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fastutil extends the Java Collections Framework by providing type-specific maps, sets, lists and priority queues with a small memory footprint and fast access and insertion; provides also big (64-bit) arrays, sets and lists, and fast, practical I/O classes for binary and text files.

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/*
	* Copyright (C) 2002-2017 Sebastiano Vigna
	*
	* 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.
	*
	*
	*
	* For the sorting and binary search code:
	*
	* Copyright (C) 1999 CERN - European Organization for Nuclear Research.
	*
	*   Permission to use, copy, modify, distribute and sell this software and
	*   its documentation for any purpose is hereby granted without fee,
	*   provided that the above copyright notice appear in all copies and that
	*   both that copyright notice and this permission notice appear in
	*   supporting documentation. CERN makes no representations about the
	*   suitability of this software for any purpose. It is provided "as is"
	*   without expressed or implied warranty.
	*/
package it.unimi.dsi.fastutil.ints;
import it.unimi.dsi.fastutil.Arrays;
import it.unimi.dsi.fastutil.Hash;
import java.util.Random;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveAction;
import java.util.concurrent.ExecutorCompletionService;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.atomic.AtomicInteger;
/**
 * A class providing static methods and objects that do useful things with
 * type-specific arrays.
 *
 * 

* In particular, the {@code forceCapacity()}, {@code ensureCapacity()}, * {@code grow()}, {@code trim()} and {@code setLength()} methods allow to * handle arrays much like array lists. This can be very useful when efficiency * (or syntactic simplicity) reasons make array lists unsuitable. * *

* Note that {@link it.unimi.dsi.fastutil.io.BinIO} and * {@link it.unimi.dsi.fastutil.io.TextIO} contain several methods make it * possible to load and save arrays of primitive types as sequences of elements * in {@link java.io.DataInput} format (i.e., not as objects) or as sequences of * lines of text. * *

Sorting

* *

* There are several sorting methods available. The main theme is that of * letting you choose the sorting algorithm you prefer (i.e., trading stability * of mergesort for no memory allocation in quicksort). Several algorithms * provide a parallel version, that will use the * {@linkplain Runtime#availableProcessors() number of cores available}. Some * algorithms also provide an explicit indirect sorting facility, which * makes it possible to sort an array using the values in another array as * comparator. * *

* All comparison-based algorithm have an implementation based on a * type-specific comparator. * *

* As a general rule, sequential radix sort is significantly faster than * quicksort or mergesort, in particular on random-looking data. In the parallel * case, up to a few cores parallel radix sort is still the fastest, but at some * point quicksort exploits parallelism better. * *

* If you are fine with not knowing exactly which algorithm will be run (in * particular, not knowing exactly whether a support array will be allocated), * the dual-pivot parallel sorts in {@link java.util.Arrays} are about 50% * faster than the classical single-pivot implementation used here. * *

* In any case, if sorting time is important I suggest that you benchmark your * sorting load with your data distribution and on your architecture. * * @see java.util.Arrays */ public final class IntArrays { private IntArrays() { } /** A static, final, empty array. */ public static final int[] EMPTY_ARRAY = {}; /** * A static, final, empty array to be used as default array in allocations. An * object distinct from {@link #EMPTY_ARRAY} makes it possible to have different * behaviors depending on whether the user required an empty allocation, or we * are just lazily delaying allocation. * * @see java.util.ArrayList */ public static final int[] DEFAULT_EMPTY_ARRAY = {}; /** * Forces an array to contain the given number of entries, preserving just a * part of the array. * * @param array * an array. * @param length * the new minimum length for this array. * @param preserve * the number of elements of the array that must be preserved in case * a new allocation is necessary. * @return an array with {@code length} entries whose first {@code preserve} * entries are the same as those of {@code array}. */ public static int[] forceCapacity(final int[] array, final int length, final int preserve) { final int t[] = new int[length]; System.arraycopy(array, 0, t, 0, preserve); return t; } /** * Ensures that an array can contain the given number of entries. * *

* If you cannot foresee whether this array will need again to be enlarged, you * should probably use {@code grow()} instead. * * @param array * an array. * @param length * the new minimum length for this array. * @return {@code array}, if it contains {@code length} entries or more; * otherwise, an array with {@code length} entries whose first * {@code array.length} entries are the same as those of {@code array}. */ public static int[] ensureCapacity(final int[] array, final int length) { return ensureCapacity(array, length, array.length); } /** * Ensures that an array can contain the given number of entries, preserving * just a part of the array. * * @param array * an array. * @param length * the new minimum length for this array. * @param preserve * the number of elements of the array that must be preserved in case * a new allocation is necessary. * @return {@code array}, if it can contain {@code length} entries or more; * otherwise, an array with {@code length} entries whose first * {@code preserve} entries are the same as those of {@code array}. */ public static int[] ensureCapacity(final int[] array, final int length, final int preserve) { return length > array.length ? forceCapacity(array, length, preserve) : array; } /** * Grows the given array to the maximum between the given length and the current * length increased by 50%, provided that the given length is larger than the * current length. * *

* If you want complete control on the array growth, you should probably use * {@code ensureCapacity()} instead. * * @param array * an array. * @param length * the new minimum length for this array. * @return {@code array}, if it can contain {@code length} entries; otherwise, * an array with max({@code length},{@code array.length}/φ) entries * whose first {@code array.length} entries are the same as those of * {@code array}. */ public static int[] grow(final int[] array, final int length) { return grow(array, length, array.length); } /** * Grows the given array to the maximum between the given length and the current * length increased by 50%, provided that the given length is larger than the * current length, preserving just a part of the array. * *

* If you want complete control on the array growth, you should probably use * {@code ensureCapacity()} instead. * * @param array * an array. * @param length * the new minimum length for this array. * @param preserve * the number of elements of the array that must be preserved in case * a new allocation is necessary. * @return {@code array}, if it can contain {@code length} entries; otherwise, * an array with max({@code length},{@code array.length}/φ) entries * whose first {@code preserve} entries are the same as those of * {@code array}. */ public static int[] grow(final int[] array, final int length, final int preserve) { if (length > array.length) { final int newLength = (int) Math .max(Math.min((long) array.length + (array.length >> 1), Arrays.MAX_ARRAY_SIZE), length); final int t[] = new int[newLength]; System.arraycopy(array, 0, t, 0, preserve); return t; } return array; } /** * Trims the given array to the given length. * * @param array * an array. * @param length * the new maximum length for the array. * @return {@code array}, if it contains {@code length} entries or less; * otherwise, an array with {@code length} entries whose entries are the * same as the first {@code length} entries of {@code array}. * */ public static int[] trim(final int[] array, final int length) { if (length >= array.length) return array; final int t[] = length == 0 ? EMPTY_ARRAY : new int[length]; System.arraycopy(array, 0, t, 0, length); return t; } /** * Sets the length of the given array. * * @param array * an array. * @param length * the new length for the array. * @return {@code array}, if it contains exactly {@code length} entries; * otherwise, if it contains more than {@code length} entries, * an array with {@code length} entries whose entries are the same as * the first {@code length} entries of {@code array}; otherwise, an * array with {@code length} entries whose first {@code array.length} * entries are the same as those of {@code array}. * */ public static int[] setLength(final int[] array, final int length) { if (length == array.length) return array; if (length < array.length) return trim(array, length); return ensureCapacity(array, length); } /** * Returns a copy of a portion of an array. * * @param array * an array. * @param offset * the first element to copy. * @param length * the number of elements to copy. * @return a new array containing {@code length} elements of {@code array} * starting at {@code offset}. */ public static int[] copy(final int[] array, final int offset, final int length) { ensureOffsetLength(array, offset, length); final int[] a = length == 0 ? EMPTY_ARRAY : new int[length]; System.arraycopy(array, offset, a, 0, length); return a; } /** * Returns a copy of an array. * * @param array * an array. * @return a copy of {@code array}. */ public static int[] copy(final int[] array) { return array.clone(); } /** * Fills the given array with the given value. * * @param array * an array. * @param value * the new value for all elements of the array. * @deprecated Please use the corresponding {@link java.util.Arrays} method. */ @Deprecated public static void fill(final int[] array, final int value) { int i = array.length; while (i-- != 0) array[i] = value; } /** * Fills a portion of the given array with the given value. * * @param array * an array. * @param from * the starting index of the portion to fill (inclusive). * @param to * the end index of the portion to fill (exclusive). * @param value * the new value for all elements of the specified portion of the * array. * @deprecated Please use the corresponding {@link java.util.Arrays} method. */ @Deprecated public static void fill(final int[] array, final int from, int to, final int value) { ensureFromTo(array, from, to); if (from == 0) while (to-- != 0) array[to] = value; else for (int i = from; i < to; i++) array[i] = value; } /** * Returns true if the two arrays are elementwise equal. * * @param a1 * an array. * @param a2 * another array. * @return true if the two arrays are of the same length, and their elements are * equal. * @deprecated Please use the corresponding {@link java.util.Arrays} method, * which is intrinsified in recent JVMs. */ @Deprecated public static boolean equals(final int[] a1, final int a2[]) { int i = a1.length; if (i != a2.length) return false; while (i-- != 0) if (!((a1[i]) == (a2[i]))) return false; return true; } /** * Ensures that a range given by its first (inclusive) and last (exclusive) * elements fits an array. * *

* This method may be used whenever an array range check is needed. * * @param a * an array. * @param from * a start index (inclusive). * @param to * an end index (exclusive). * @throws IllegalArgumentException * if {@code from} is greater than {@code to}. * @throws ArrayIndexOutOfBoundsException * if {@code from} or {@code to} are greater than the array length * or negative. */ public static void ensureFromTo(final int[] a, final int from, final int to) { Arrays.ensureFromTo(a.length, from, to); } /** * Ensures that a range given by an offset and a length fits an array. * *

* This method may be used whenever an array range check is needed. * * @param a * an array. * @param offset * a start index. * @param length * a length (the number of elements in the range). * @throws IllegalArgumentException * if {@code length} is negative. * @throws ArrayIndexOutOfBoundsException * if {@code offset} is negative or {@code offset}+{@code length} is * greater than the array length. */ public static void ensureOffsetLength(final int[] a, final int offset, final int length) { Arrays.ensureOffsetLength(a.length, offset, length); } /** * Ensures that two arrays are of the same length. * * @param a * an array. * @param b * another array. * @throws IllegalArgumentException * if the two argument arrays are not of the same length. */ public static void ensureSameLength(final int[] a, final int[] b) { if (a.length != b.length) throw new IllegalArgumentException("Array size mismatch: " + a.length + " != " + b.length); } private static final int QUICKSORT_NO_REC = 16; private static final int PARALLEL_QUICKSORT_NO_FORK = 8192; private static final int QUICKSORT_MEDIAN_OF_9 = 128; private static final int MERGESORT_NO_REC = 16; /** * Swaps two elements of an anrray. * * @param x * an array. * @param a * a position in {@code x}. * @param b * another position in {@code x}. */ public static void swap(final int x[], final int a, final int b) { final int t = x[a]; x[a] = x[b]; x[b] = t; } /** * Swaps two sequences of elements of an array. * * @param x * an array. * @param a * a position in {@code x}. * @param b * another position in {@code x}. * @param n * the number of elements to exchange starting at {@code a} and * {@code b}. */ public static void swap(final int[] x, int a, int b, final int n) { for (int i = 0; i < n; i++, a++, b++) swap(x, a, b); } private static int med3(final int x[], final int a, final int b, final int c, IntComparator comp) { final int ab = comp.compare(x[a], x[b]); final int ac = comp.compare(x[a], x[c]); final int bc = comp.compare(x[b], x[c]); return (ab < 0 ? (bc < 0 ? b : ac < 0 ? c : a) : (bc > 0 ? b : ac > 0 ? c : a)); } private static void selectionSort(final int[] a, final int from, final int to, final IntComparator comp) { for (int i = from; i < to - 1; i++) { int m = i; for (int j = i + 1; j < to; j++) if (comp.compare(a[j], a[m]) < 0) m = j; if (m != i) { final int u = a[i]; a[i] = a[m]; a[m] = u; } } } private static void insertionSort(final int[] a, final int from, final int to, final IntComparator comp) { for (int i = from; ++i < to;) { int t = a[i]; int j = i; for (int u = a[j - 1]; comp.compare(t, u) < 0; u = a[--j - 1]) { a[j] = u; if (from == j - 1) { --j; break; } } a[j] = t; } } /** * Sorts the specified range of elements according to the order induced by the * specified comparator using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param comp * the comparator to determine the sorting order. * */ public static void quickSort(final int[] x, final int from, final int to, final IntComparator comp) { final int len = to - from; // Selection sort on smallest arrays if (len < QUICKSORT_NO_REC) { selectionSort(x, from, to, comp); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; if (len > QUICKSORT_MEDIAN_OF_9) { // Big arrays, pseudomedian of 9 int s = len / 8; l = med3(x, l, l + s, l + 2 * s, comp); m = med3(x, m - s, m, m + s, comp); n = med3(x, n - 2 * s, n - s, n, comp); } m = med3(x, l, m, n, comp); // Mid-size, med of 3 final int v = x[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = comp.compare(x[b], v)) <= 0) { if (comparison == 0) swap(x, a++, b); b++; } while (c >= b && (comparison = comp.compare(x[c], v)) >= 0) { if (comparison == 0) swap(x, c, d--); c--; } if (b > c) break; swap(x, b++, c--); } // Swap partition elements back to middle int s; s = Math.min(a - from, b - a); swap(x, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, b, to - s, s); // Recursively sort non-partition-elements if ((s = b - a) > 1) quickSort(x, from, from + s, comp); if ((s = d - c) > 1) quickSort(x, to - s, to, comp); } /** * Sorts an array according to the order induced by the specified comparator * using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param x * the array to be sorted. * @param comp * the comparator to determine the sorting order. * */ public static void quickSort(final int[] x, final IntComparator comp) { quickSort(x, 0, x.length, comp); } protected static class ForkJoinQuickSortComp extends RecursiveAction { private static final long serialVersionUID = 1L; private final int from; private final int to; private final int[] x; private final IntComparator comp; public ForkJoinQuickSortComp(final int[] x, final int from, final int to, final IntComparator comp) { this.from = from; this.to = to; this.x = x; this.comp = comp; } @Override protected void compute() { final int[] x = this.x; final int len = to - from; if (len < PARALLEL_QUICKSORT_NO_FORK) { quickSort(x, from, to, comp); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; int s = len / 8; l = med3(x, l, l + s, l + 2 * s, comp); m = med3(x, m - s, m, m + s, comp); n = med3(x, n - 2 * s, n - s, n, comp); m = med3(x, l, m, n, comp); final int v = x[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = comp.compare(x[b], v)) <= 0) { if (comparison == 0) swap(x, a++, b); b++; } while (c >= b && (comparison = comp.compare(x[c], v)) >= 0) { if (comparison == 0) swap(x, c, d--); c--; } if (b > c) break; swap(x, b++, c--); } // Swap partition elements back to middle int t; s = Math.min(a - from, b - a); swap(x, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, b, to - s, s); // Recursively sort non-partition-elements s = b - a; t = d - c; if (s > 1 && t > 1) invokeAll(new ForkJoinQuickSortComp(x, from, from + s, comp), new ForkJoinQuickSortComp(x, to - t, to, comp)); else if (s > 1) invokeAll(new ForkJoinQuickSortComp(x, from, from + s, comp)); else invokeAll(new ForkJoinQuickSortComp(x, to - t, to, comp)); } } /** * Sorts the specified range of elements according to the order induced by the * specified comparator using a parallel quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param comp * the comparator to determine the sorting order. */ public static void parallelQuickSort(final int[] x, final int from, final int to, final IntComparator comp) { if (to - from < PARALLEL_QUICKSORT_NO_FORK) quickSort(x, from, to, comp); else { final ForkJoinPool pool = new ForkJoinPool(Runtime.getRuntime().availableProcessors()); pool.invoke(new ForkJoinQuickSortComp(x, from, to, comp)); pool.shutdown(); } } /** * Sorts an array according to the order induced by the specified comparator * using a parallel quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the array to be sorted. * @param comp * the comparator to determine the sorting order. */ public static void parallelQuickSort(final int[] x, final IntComparator comp) { parallelQuickSort(x, 0, x.length, comp); } private static int med3(final int x[], final int a, final int b, final int c) { final int ab = (Integer.compare((x[a]), (x[b]))); final int ac = (Integer.compare((x[a]), (x[c]))); final int bc = (Integer.compare((x[b]), (x[c]))); return (ab < 0 ? (bc < 0 ? b : ac < 0 ? c : a) : (bc > 0 ? b : ac > 0 ? c : a)); } private static void selectionSort(final int[] a, final int from, final int to) { for (int i = from; i < to - 1; i++) { int m = i; for (int j = i + 1; j < to; j++) if (((a[j]) < (a[m]))) m = j; if (m != i) { final int u = a[i]; a[i] = a[m]; a[m] = u; } } } private static void insertionSort(final int[] a, final int from, final int to) { for (int i = from; ++i < to;) { int t = a[i]; int j = i; for (int u = a[j - 1]; ((t) < (u)); u = a[--j - 1]) { a[j] = u; if (from == j - 1) { --j; break; } } a[j] = t; } } /** * Sorts the specified range of elements according to the natural ascending * order using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void quickSort(final int[] x, final int from, final int to) { final int len = to - from; // Selection sort on smallest arrays if (len < QUICKSORT_NO_REC) { selectionSort(x, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; if (len > QUICKSORT_MEDIAN_OF_9) { // Big arrays, pseudomedian of 9 int s = len / 8; l = med3(x, l, l + s, l + 2 * s); m = med3(x, m - s, m, m + s); n = med3(x, n - 2 * s, n - s, n); } m = med3(x, l, m, n); // Mid-size, med of 3 final int v = x[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = (Integer.compare((x[b]), (v)))) <= 0) { if (comparison == 0) swap(x, a++, b); b++; } while (c >= b && (comparison = (Integer.compare((x[c]), (v)))) >= 0) { if (comparison == 0) swap(x, c, d--); c--; } if (b > c) break; swap(x, b++, c--); } // Swap partition elements back to middle int s; s = Math.min(a - from, b - a); swap(x, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, b, to - s, s); // Recursively sort non-partition-elements if ((s = b - a) > 1) quickSort(x, from, from + s); if ((s = d - c) > 1) quickSort(x, to - s, to); } /** * Sorts an array according to the natural ascending order using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param x * the array to be sorted. * */ public static void quickSort(final int[] x) { quickSort(x, 0, x.length); } protected static class ForkJoinQuickSort extends RecursiveAction { private static final long serialVersionUID = 1L; private final int from; private final int to; private final int[] x; public ForkJoinQuickSort(final int[] x, final int from, final int to) { this.from = from; this.to = to; this.x = x; } @Override protected void compute() { final int[] x = this.x; final int len = to - from; if (len < PARALLEL_QUICKSORT_NO_FORK) { quickSort(x, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; int s = len / 8; l = med3(x, l, l + s, l + 2 * s); m = med3(x, m - s, m, m + s); n = med3(x, n - 2 * s, n - s, n); m = med3(x, l, m, n); final int v = x[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = (Integer.compare((x[b]), (v)))) <= 0) { if (comparison == 0) swap(x, a++, b); b++; } while (c >= b && (comparison = (Integer.compare((x[c]), (v)))) >= 0) { if (comparison == 0) swap(x, c, d--); c--; } if (b > c) break; swap(x, b++, c--); } // Swap partition elements back to middle int t; s = Math.min(a - from, b - a); swap(x, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, b, to - s, s); // Recursively sort non-partition-elements s = b - a; t = d - c; if (s > 1 && t > 1) invokeAll(new ForkJoinQuickSort(x, from, from + s), new ForkJoinQuickSort(x, to - t, to)); else if (s > 1) invokeAll(new ForkJoinQuickSort(x, from, from + s)); else invokeAll(new ForkJoinQuickSort(x, to - t, to)); } } /** * Sorts the specified range of elements according to the natural ascending * order using a parallel quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void parallelQuickSort(final int[] x, final int from, final int to) { if (to - from < PARALLEL_QUICKSORT_NO_FORK) quickSort(x, from, to); else { final ForkJoinPool pool = new ForkJoinPool(Runtime.getRuntime().availableProcessors()); pool.invoke(new ForkJoinQuickSort(x, from, to)); pool.shutdown(); } } /** * Sorts an array according to the natural ascending order using a parallel * quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the array to be sorted. * */ public static void parallelQuickSort(final int[] x) { parallelQuickSort(x, 0, x.length); } private static int med3Indirect(final int perm[], final int x[], final int a, final int b, final int c) { final int aa = x[perm[a]]; final int bb = x[perm[b]]; final int cc = x[perm[c]]; final int ab = (Integer.compare((aa), (bb))); final int ac = (Integer.compare((aa), (cc))); final int bc = (Integer.compare((bb), (cc))); return (ab < 0 ? (bc < 0 ? b : ac < 0 ? c : a) : (bc > 0 ? b : ac > 0 ? c : a)); } private static void insertionSortIndirect(final int[] perm, final int[] a, final int from, final int to) { for (int i = from; ++i < to;) { int t = perm[i]; int j = i; for (int u = perm[j - 1]; ((a[t]) < (a[u])); u = perm[--j - 1]) { perm[j] = u; if (from == j - 1) { --j; break; } } perm[j] = t; } } /** * Sorts the specified range of elements according to the natural ascending * order using indirect quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code x[perm[i]] ≤ x[perm[i + 1]]}. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param perm * a permutation array indexing {@code x}. * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void quickSortIndirect(final int[] perm, final int[] x, final int from, final int to) { final int len = to - from; // Selection sort on smallest arrays if (len < QUICKSORT_NO_REC) { insertionSortIndirect(perm, x, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; if (len > QUICKSORT_MEDIAN_OF_9) { // Big arrays, pseudomedian of 9 int s = len / 8; l = med3Indirect(perm, x, l, l + s, l + 2 * s); m = med3Indirect(perm, x, m - s, m, m + s); n = med3Indirect(perm, x, n - 2 * s, n - s, n); } m = med3Indirect(perm, x, l, m, n); // Mid-size, med of 3 final int v = x[perm[m]]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = (Integer.compare((x[perm[b]]), (v)))) <= 0) { if (comparison == 0) IntArrays.swap(perm, a++, b); b++; } while (c >= b && (comparison = (Integer.compare((x[perm[c]]), (v)))) >= 0) { if (comparison == 0) IntArrays.swap(perm, c, d--); c--; } if (b > c) break; IntArrays.swap(perm, b++, c--); } // Swap partition elements back to middle int s; s = Math.min(a - from, b - a); IntArrays.swap(perm, from, b - s, s); s = Math.min(d - c, to - d - 1); IntArrays.swap(perm, b, to - s, s); // Recursively sort non-partition-elements if ((s = b - a) > 1) quickSortIndirect(perm, x, from, from + s); if ((s = d - c) > 1) quickSortIndirect(perm, x, to - s, to); } /** * Sorts an array according to the natural ascending order using indirect * quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code x[perm[i]] ≤ x[perm[i + 1]]}. * *

* Note that this implementation does not allocate any object, contrarily to the * implementation used to sort primitive types in {@link java.util.Arrays}, * which switches to mergesort on large inputs. * * @param perm * a permutation array indexing {@code x}. * @param x * the array to be sorted. */ public static void quickSortIndirect(final int perm[], final int[] x) { quickSortIndirect(perm, x, 0, x.length); } protected static class ForkJoinQuickSortIndirect extends RecursiveAction { private static final long serialVersionUID = 1L; private final int from; private final int to; private final int[] perm; private final int[] x; public ForkJoinQuickSortIndirect(final int perm[], final int[] x, final int from, final int to) { this.from = from; this.to = to; this.x = x; this.perm = perm; } @Override protected void compute() { final int[] x = this.x; final int len = to - from; if (len < PARALLEL_QUICKSORT_NO_FORK) { quickSortIndirect(perm, x, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; int s = len / 8; l = med3Indirect(perm, x, l, l + s, l + 2 * s); m = med3Indirect(perm, x, m - s, m, m + s); n = med3Indirect(perm, x, n - 2 * s, n - s, n); m = med3Indirect(perm, x, l, m, n); final int v = x[perm[m]]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison; while (b <= c && (comparison = (Integer.compare((x[perm[b]]), (v)))) <= 0) { if (comparison == 0) IntArrays.swap(perm, a++, b); b++; } while (c >= b && (comparison = (Integer.compare((x[perm[c]]), (v)))) >= 0) { if (comparison == 0) IntArrays.swap(perm, c, d--); c--; } if (b > c) break; IntArrays.swap(perm, b++, c--); } // Swap partition elements back to middle int t; s = Math.min(a - from, b - a); IntArrays.swap(perm, from, b - s, s); s = Math.min(d - c, to - d - 1); IntArrays.swap(perm, b, to - s, s); // Recursively sort non-partition-elements s = b - a; t = d - c; if (s > 1 && t > 1) invokeAll(new ForkJoinQuickSortIndirect(perm, x, from, from + s), new ForkJoinQuickSortIndirect(perm, x, to - t, to)); else if (s > 1) invokeAll(new ForkJoinQuickSortIndirect(perm, x, from, from + s)); else invokeAll(new ForkJoinQuickSortIndirect(perm, x, to - t, to)); } } /** * Sorts the specified range of elements according to the natural ascending * order using a parallel indirect quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code x[perm[i]] ≤ x[perm[i + 1]]}. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param perm * a permutation array indexing {@code x}. * @param x * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void parallelQuickSortIndirect(final int[] perm, final int[] x, final int from, final int to) { if (to - from < PARALLEL_QUICKSORT_NO_FORK) quickSortIndirect(perm, x, from, to); else { final ForkJoinPool pool = new ForkJoinPool(Runtime.getRuntime().availableProcessors()); pool.invoke(new ForkJoinQuickSortIndirect(perm, x, from, to)); pool.shutdown(); } } /** * Sorts an array according to the natural ascending order using a parallel * indirect quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code x[perm[i]] ≤ x[perm[i + 1]]}. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param perm * a permutation array indexing {@code x}. * @param x * the array to be sorted. * */ public static void parallelQuickSortIndirect(final int perm[], final int[] x) { parallelQuickSortIndirect(perm, x, 0, x.length); } /** * Stabilizes a permutation. * *

* This method can be used to stabilize the permutation generated by an indirect * sorting, assuming that initially the permutation array was in ascending order * (e.g., the identity, as usually happens). This method scans the permutation, * and for each non-singleton block of elements with the same associated values * in {@code x}, permutes them in ascending order. The resulting permutation * corresponds to a stable sort. * *

* Usually combining an unstable indirect sort and this method is more efficient * than using a stable sort, as most stable sort algorithms require a support * array. * *

* More precisely, assuming that {@code x[perm[i]] ≤ x[perm[i + 1]]}, after * stabilization we will also have that {@code x[perm[i]] = x[perm[i + 1]]} * implies {@code perm[i] ≤ perm[i + 1]}. * * @param perm * a permutation array indexing {@code x} so that it is sorted. * @param x * the sorted array to be stabilized. * @param from * the index of the first element (inclusive) to be stabilized. * @param to * the index of the last element (exclusive) to be stabilized. */ public static void stabilize(final int perm[], final int[] x, final int from, final int to) { int curr = from; for (int i = from + 1; i < to; i++) { if (x[perm[i]] != x[perm[curr]]) { if (i - curr > 1) IntArrays.parallelQuickSort(perm, curr, i); curr = i; } } if (to - curr > 1) IntArrays.parallelQuickSort(perm, curr, to); } /** * Stabilizes a permutation. * *

* This method can be used to stabilize the permutation generated by an indirect * sorting, assuming that initially the permutation array was in ascending order * (e.g., the identity, as usually happens). This method scans the permutation, * and for each non-singleton block of elements with the same associated values * in {@code x}, permutes them in ascending order. The resulting permutation * corresponds to a stable sort. * *

* Usually combining an unstable indirect sort and this method is more efficient * than using a stable sort, as most stable sort algorithms require a support * array. * *

* More precisely, assuming that {@code x[perm[i]] ≤ x[perm[i + 1]]}, after * stabilization we will also have that {@code x[perm[i]] = x[perm[i + 1]]} * implies {@code perm[i] ≤ perm[i + 1]}. * * @param perm * a permutation array indexing {@code x} so that it is sorted. * @param x * the sorted array to be stabilized. */ public static void stabilize(final int perm[], final int[] x) { stabilize(perm, x, 0, perm.length); } private static int med3(final int x[], final int[] y, final int a, final int b, final int c) { int t; final int ab = (t = (Integer.compare((x[a]), (x[b])))) == 0 ? (Integer.compare((y[a]), (y[b]))) : t; final int ac = (t = (Integer.compare((x[a]), (x[c])))) == 0 ? (Integer.compare((y[a]), (y[c]))) : t; final int bc = (t = (Integer.compare((x[b]), (x[c])))) == 0 ? (Integer.compare((y[b]), (y[c]))) : t; return (ab < 0 ? (bc < 0 ? b : ac < 0 ? c : a) : (bc > 0 ? b : ac > 0 ? c : a)); } private static void swap(final int x[], final int[] y, final int a, final int b) { final int t = x[a]; final int u = y[a]; x[a] = x[b]; y[a] = y[b]; x[b] = t; y[b] = u; } private static void swap(final int[] x, final int[] y, int a, int b, final int n) { for (int i = 0; i < n; i++, a++, b++) swap(x, y, a, b); } private static void selectionSort(final int[] a, final int[] b, final int from, final int to) { for (int i = from; i < to - 1; i++) { int m = i, u; for (int j = i + 1; j < to; j++) if ((u = (Integer.compare((a[j]), (a[m])))) < 0 || u == 0 && ((b[j]) < (b[m]))) m = j; if (m != i) { int t = a[i]; a[i] = a[m]; a[m] = t; t = b[i]; b[i] = b[m]; b[m] = t; } } } /** * Sorts the specified range of elements of two arrays according to the natural * lexicographical ascending order using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code x[i] < x[i + 1]} or x[i] * == x[i + 1] and {@code y[i] ≤ y[i + 1]}. * * @param x * the first array to be sorted. * @param y * the second array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void quickSort(final int[] x, final int[] y, final int from, final int to) { final int len = to - from; if (len < QUICKSORT_NO_REC) { selectionSort(x, y, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; if (len > QUICKSORT_MEDIAN_OF_9) { // Big arrays, pseudomedian of 9 int s = len / 8; l = med3(x, y, l, l + s, l + 2 * s); m = med3(x, y, m - s, m, m + s); n = med3(x, y, n - 2 * s, n - s, n); } m = med3(x, y, l, m, n); // Mid-size, med of 3 final int v = x[m], w = y[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison, t; while (b <= c && (comparison = (t = (Integer.compare((x[b]), (v)))) == 0 ? (Integer.compare((y[b]), (w))) : t) <= 0) { if (comparison == 0) swap(x, y, a++, b); b++; } while (c >= b && (comparison = (t = (Integer.compare((x[c]), (v)))) == 0 ? (Integer.compare((y[c]), (w))) : t) >= 0) { if (comparison == 0) swap(x, y, c, d--); c--; } if (b > c) break; swap(x, y, b++, c--); } // Swap partition elements back to middle int s; s = Math.min(a - from, b - a); swap(x, y, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, y, b, to - s, s); // Recursively sort non-partition-elements if ((s = b - a) > 1) quickSort(x, y, from, from + s); if ((s = d - c) > 1) quickSort(x, y, to - s, to); } /** * Sorts two arrays according to the natural lexicographical ascending order * using quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code x[i] < x[i + 1]} or x[i] * == x[i + 1] and {@code y[i] ≤ y[i + 1]}. * * @param x * the first array to be sorted. * @param y * the second array to be sorted. */ public static void quickSort(final int[] x, final int[] y) { ensureSameLength(x, y); quickSort(x, y, 0, x.length); } protected static class ForkJoinQuickSort2 extends RecursiveAction { private static final long serialVersionUID = 1L; private final int from; private final int to; private final int[] x, y; public ForkJoinQuickSort2(final int[] x, final int[] y, final int from, final int to) { this.from = from; this.to = to; this.x = x; this.y = y; } @Override protected void compute() { final int[] x = this.x; final int[] y = this.y; final int len = to - from; if (len < PARALLEL_QUICKSORT_NO_FORK) { quickSort(x, y, from, to); return; } // Choose a partition element, v int m = from + len / 2; int l = from; int n = to - 1; int s = len / 8; l = med3(x, y, l, l + s, l + 2 * s); m = med3(x, y, m - s, m, m + s); n = med3(x, y, n - 2 * s, n - s, n); m = med3(x, y, l, m, n); final int v = x[m], w = y[m]; // Establish Invariant: v* (v)* v* int a = from, b = a, c = to - 1, d = c; while (true) { int comparison, t; while (b <= c && (comparison = (t = (Integer.compare((x[b]), (v)))) == 0 ? (Integer.compare((y[b]), (w))) : t) <= 0) { if (comparison == 0) swap(x, y, a++, b); b++; } while (c >= b && (comparison = (t = (Integer.compare((x[c]), (v)))) == 0 ? (Integer.compare((y[c]), (w))) : t) >= 0) { if (comparison == 0) swap(x, y, c, d--); c--; } if (b > c) break; swap(x, y, b++, c--); } // Swap partition elements back to middle int t; s = Math.min(a - from, b - a); swap(x, y, from, b - s, s); s = Math.min(d - c, to - d - 1); swap(x, y, b, to - s, s); s = b - a; t = d - c; // Recursively sort non-partition-elements if (s > 1 && t > 1) invokeAll(new ForkJoinQuickSort2(x, y, from, from + s), new ForkJoinQuickSort2(x, y, to - t, to)); else if (s > 1) invokeAll(new ForkJoinQuickSort2(x, y, from, from + s)); else invokeAll(new ForkJoinQuickSort2(x, y, to - t, to)); } } /** * Sorts the specified range of elements of two arrays according to the natural * lexicographical ascending order using a parallel quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code x[i] < x[i + 1]} or x[i] * == x[i + 1] and {@code y[i] ≤ y[i + 1]}. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the first array to be sorted. * @param y * the second array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void parallelQuickSort(final int[] x, final int[] y, final int from, final int to) { if (to - from < PARALLEL_QUICKSORT_NO_FORK) quickSort(x, y, from, to); final ForkJoinPool pool = new ForkJoinPool(Runtime.getRuntime().availableProcessors()); pool.invoke(new ForkJoinQuickSort2(x, y, from, to)); pool.shutdown(); } /** * Sorts two arrays according to the natural lexicographical ascending order * using a parallel quicksort. * *

* The sorting algorithm is a tuned quicksort adapted from Jon L. Bentley and M. * Douglas McIlroy, “Engineering a Sort Function”, Software: * Practice and Experience, 23(11), pages 1249−1265, 1993. * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code x[i] < x[i + 1]} or x[i] * == x[i + 1] and {@code y[i] ≤ y[i + 1]}. * *

* This implementation uses a {@link ForkJoinPool} executor service with * {@link Runtime#availableProcessors()} parallel threads. * * @param x * the first array to be sorted. * @param y * the second array to be sorted. */ public static void parallelQuickSort(final int[] x, final int[] y) { ensureSameLength(x, y); parallelQuickSort(x, y, 0, x.length); } /** * Sorts the specified range of elements according to the natural ascending * order using mergesort, using a given pre-filled support array. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. Moreover, no support arrays will be * allocated. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param supp * a support array containing at least {@code to} elements, and whose * entries are identical to those of {@code a} in the specified * range. */ public static void mergeSort(final int a[], final int from, final int to, final int supp[]) { int len = to - from; // Insertion sort on smallest arrays if (len < MERGESORT_NO_REC) { insertionSort(a, from, to); return; } // Recursively sort halves of a into supp final int mid = (from + to) >>> 1; mergeSort(supp, from, mid, a); mergeSort(supp, mid, to, a); // If list is already sorted, just copy from supp to a. This is an // optimization that results in faster sorts for nearly ordered lists. if (((supp[mid - 1]) <= (supp[mid]))) { System.arraycopy(supp, from, a, from, len); return; } // Merge sorted halves (now in supp) into a for (int i = from, p = from, q = mid; i < to; i++) { if (q >= to || p < mid && ((supp[p]) <= (supp[q]))) a[i] = supp[p++]; else a[i] = supp[q++]; } } /** * Sorts the specified range of elements according to the natural ascending * order using mergesort. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. An array as large as {@code a} will be * allocated by this method. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void mergeSort(final int a[], final int from, final int to) { mergeSort(a, from, to, a.clone()); } /** * Sorts an array according to the natural ascending order using mergesort. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. An array as large as {@code a} will be * allocated by this method. * * @param a * the array to be sorted. */ public static void mergeSort(final int a[]) { mergeSort(a, 0, a.length); } /** * Sorts the specified range of elements according to the order induced by the * specified comparator using mergesort, using a given pre-filled support array. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. Moreover, no support arrays will be * allocated. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param comp * the comparator to determine the sorting order. * @param supp * a support array containing at least {@code to} elements, and whose * entries are identical to those of {@code a} in the specified * range. */ public static void mergeSort(final int a[], final int from, final int to, IntComparator comp, final int supp[]) { int len = to - from; // Insertion sort on smallest arrays if (len < MERGESORT_NO_REC) { insertionSort(a, from, to, comp); return; } // Recursively sort halves of a into supp final int mid = (from + to) >>> 1; mergeSort(supp, from, mid, comp, a); mergeSort(supp, mid, to, comp, a); // If list is already sorted, just copy from supp to a. This is an // optimization that results in faster sorts for nearly ordered lists. if (comp.compare(supp[mid - 1], supp[mid]) <= 0) { System.arraycopy(supp, from, a, from, len); return; } // Merge sorted halves (now in supp) into a for (int i = from, p = from, q = mid; i < to; i++) { if (q >= to || p < mid && comp.compare(supp[p], supp[q]) <= 0) a[i] = supp[p++]; else a[i] = supp[q++]; } } /** * Sorts the specified range of elements according to the order induced by the * specified comparator using mergesort. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. An array as large as {@code a} will be * allocated by this method. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param comp * the comparator to determine the sorting order. */ public static void mergeSort(final int a[], final int from, final int to, IntComparator comp) { mergeSort(a, from, to, comp, a.clone()); } /** * Sorts an array according to the order induced by the specified comparator * using mergesort. * *

* This sort is guaranteed to be stable: equal elements will not be * reordered as a result of the sort. An array as large as {@code a} will be * allocated by this method. * * @param a * the array to be sorted. * @param comp * the comparator to determine the sorting order. */ public static void mergeSort(final int a[], IntComparator comp) { mergeSort(a, 0, a.length, comp); } /** * Searches a range of the specified array for the specified value using the * binary search algorithm. The range must be sorted prior to making this call. * If it is not sorted, the results are undefined. If the range contains * multiple elements with the specified value, there is no guarantee which one * will be found. * * @param a * the array to be searched. * @param from * the index of the first element (inclusive) to be searched. * @param to * the index of the last element (exclusive) to be searched. * @param key * the value to be searched for. * @return index of the search key, if it is contained in the array; otherwise, * {@code (-(insertion point) - 1)}. The insertion point * is defined as the the point at which the value would be inserted into * the array: the index of the first element greater than the key, or * the length of the array, if all elements in the array are less than * the specified key. Note that this guarantees that the return value * will be ≥ 0 if and only if the key is found. * @see java.util.Arrays */ public static int binarySearch(final int[] a, int from, int to, final int key) { int midVal; to--; while (from <= to) { final int mid = (from + to) >>> 1; midVal = a[mid]; if (midVal < key) from = mid + 1; else if (midVal > key) to = mid - 1; else return mid; } return -(from + 1); } /** * Searches an array for the specified value using the binary search algorithm. * The range must be sorted prior to making this call. If it is not sorted, the * results are undefined. If the range contains multiple elements with the * specified value, there is no guarantee which one will be found. * * @param a * the array to be searched. * @param key * the value to be searched for. * @return index of the search key, if it is contained in the array; otherwise, * {@code (-(insertion point) - 1)}. The insertion point * is defined as the the point at which the value would be inserted into * the array: the index of the first element greater than the key, or * the length of the array, if all elements in the array are less than * the specified key. Note that this guarantees that the return value * will be ≥ 0 if and only if the key is found. * @see java.util.Arrays */ public static int binarySearch(final int[] a, final int key) { return binarySearch(a, 0, a.length, key); } /** * Searches a range of the specified array for the specified value using the * binary search algorithm and a specified comparator. The range must be sorted * following the comparator prior to making this call. If it is not sorted, the * results are undefined. If the range contains multiple elements with the * specified value, there is no guarantee which one will be found. * * @param a * the array to be searched. * @param from * the index of the first element (inclusive) to be searched. * @param to * the index of the last element (exclusive) to be searched. * @param key * the value to be searched for. * @param c * a comparator. * @return index of the search key, if it is contained in the array; otherwise, * {@code (-(insertion point) - 1)}. The insertion point * is defined as the the point at which the value would be inserted into * the array: the index of the first element greater than the key, or * the length of the array, if all elements in the array are less than * the specified key. Note that this guarantees that the return value * will be ≥ 0 if and only if the key is found. * @see java.util.Arrays */ public static int binarySearch(final int[] a, int from, int to, final int key, final IntComparator c) { int midVal; to--; while (from <= to) { final int mid = (from + to) >>> 1; midVal = a[mid]; final int cmp = c.compare(midVal, key); if (cmp < 0) from = mid + 1; else if (cmp > 0) to = mid - 1; else return mid; // key found } return -(from + 1); } /** * Searches an array for the specified value using the binary search algorithm * and a specified comparator. The range must be sorted following the comparator * prior to making this call. If it is not sorted, the results are undefined. If * the range contains multiple elements with the specified value, there is no * guarantee which one will be found. * * @param a * the array to be searched. * @param key * the value to be searched for. * @param c * a comparator. * @return index of the search key, if it is contained in the array; otherwise, * {@code (-(insertion point) - 1)}. The insertion point * is defined as the the point at which the value would be inserted into * the array: the index of the first element greater than the key, or * the length of the array, if all elements in the array are less than * the specified key. Note that this guarantees that the return value * will be ≥ 0 if and only if the key is found. * @see java.util.Arrays */ public static int binarySearch(final int[] a, final int key, final IntComparator c) { return binarySearch(a, 0, a.length, key, c); } /** The size of a digit used during radix sort (must be a power of 2). */ private static final int DIGIT_BITS = 8; /** The mask to extract a digit of {@link #DIGIT_BITS} bits. */ private static final int DIGIT_MASK = (1 << DIGIT_BITS) - 1; /** The number of digits per element. */ private static final int DIGITS_PER_ELEMENT = Integer.SIZE / DIGIT_BITS; private static final int RADIXSORT_NO_REC = 1024; private static final int PARALLEL_RADIXSORT_NO_FORK = 1024; /** * This method fixes negative numbers so that the combination * exponent/significand is lexicographically sorted. */ /** * Sorts the specified array using radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This implementation is significantly faster than quicksort already at small * sizes (say, more than 10000 elements), but it can only sort in ascending * order. * * @param a * the array to be sorted. */ public static void radixSort(final int[] a) { radixSort(a, 0, a.length); } /** * Sorts the specified range of an array using radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This implementation is significantly faster than quicksort already at small * sizes (say, more than 10000 elements), but it can only sort in ascending * order. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void radixSort(final int[] a, final int from, final int to) { if (to - from < RADIXSORT_NO_REC) { quickSort(a, from, to); return; } final int maxLevel = DIGITS_PER_ELEMENT - 1; final int stackSize = ((1 << DIGIT_BITS) - 1) * (DIGITS_PER_ELEMENT - 1) + 1; int stackPos = 0; final int[] offsetStack = new int[stackSize]; final int[] lengthStack = new int[stackSize]; final int[] levelStack = new int[stackSize]; offsetStack[stackPos] = from; lengthStack[stackPos] = to - from; levelStack[stackPos++] = 0; final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; while (stackPos > 0) { final int first = offsetStack[--stackPos]; final int length = lengthStack[stackPos]; final int level = levelStack[stackPos]; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the shift // that extract the // right byte from a // key // Count keys. for (int i = first + length; i-- != first;) count[((a[i]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = a[i]; c = ((t) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { final int z = t; t = a[d]; a[d] = z; c = ((t) >>> shift & DIGIT_MASK ^ signMask); } a[i] = t; } if (level < maxLevel && count[c] > 1) { if (count[c] < RADIXSORT_NO_REC) quickSort(a, i, i + count[c]); else { offsetStack[stackPos] = i; lengthStack[stackPos] = count[c]; levelStack[stackPos++] = level + 1; } } } } } protected static final class Segment { protected final int offset, length, level; protected Segment(final int offset, final int length, final int level) { this.offset = offset; this.length = length; this.level = level; } @Override public String toString() { return "Segment [offset=" + offset + ", length=" + length + ", level=" + level + "]"; } } protected static final Segment POISON_PILL = new Segment(-1, -1, -1); /** * Sorts the specified range of an array using parallel radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void parallelRadixSort(final int[] a, final int from, final int to) { if (to - from < PARALLEL_RADIXSORT_NO_FORK) { quickSort(a, from, to); return; } final int maxLevel = DIGITS_PER_ELEMENT - 1; final LinkedBlockingQueue queue = new LinkedBlockingQueue<>(); queue.add(new Segment(from, to - from, 0)); final AtomicInteger queueSize = new AtomicInteger(1); final int numberOfThreads = Runtime.getRuntime().availableProcessors(); final ExecutorService executorService = Executors.newFixedThreadPool(numberOfThreads, Executors.defaultThreadFactory()); final ExecutorCompletionService executorCompletionService = new ExecutorCompletionService<>( executorService); for (int j = numberOfThreads; j-- != 0;) executorCompletionService.submit(() -> { final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; for (;;) { if (queueSize.get() == 0) for (int i = numberOfThreads; i-- != 0;) queue.add(POISON_PILL); final Segment segment = queue.take(); if (segment == POISON_PILL) return null; final int first = segment.offset; final int length = segment.length; final int level = segment.level; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the // shift // that // extract // the right // byte from // a key // Count keys. for (int i = first + length; i-- != first;) count[((a[i]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = a[i]; c = ((t) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { while ((d = --pos[c]) > i) { final int z = t; t = a[d]; a[d] = z; c = ((t) >>> shift & DIGIT_MASK ^ signMask); } a[i] = t; } if (level < maxLevel && count[c] > 1) { if (count[c] < PARALLEL_RADIXSORT_NO_FORK) quickSort(a, i, i + count[c]); else { queueSize.incrementAndGet(); queue.add(new Segment(i, count[c], level + 1)); } } } queueSize.decrementAndGet(); } }); Throwable problem = null; for (int i = numberOfThreads; i-- != 0;) try { executorCompletionService.take().get(); } catch (Exception e) { problem = e.getCause(); // We keep only the last one. They will be logged anyway. } executorService.shutdown(); if (problem != null) throw (problem instanceof RuntimeException) ? (RuntimeException) problem : new RuntimeException(problem); } /** * Sorts the specified array using parallel radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param a * the array to be sorted. */ public static void parallelRadixSort(final int[] a) { parallelRadixSort(a, 0, a.length); } /** * Sorts the specified array using indirect radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]}. * *

* This implementation will allocate, in the stable case, a support array as * large as {@code perm} (note that the stable version is slightly faster). * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param stable * whether the sorting algorithm should be stable. */ public static void radixSortIndirect(final int[] perm, final int[] a, final boolean stable) { radixSortIndirect(perm, a, 0, perm.length, stable); } /** * Sorts the specified array using indirect radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]}. * *

* This implementation will allocate, in the stable case, a support array as * large as {@code perm} (note that the stable version is slightly faster). * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param from * the index of the first element of {@code perm} (inclusive) to be * permuted. * @param to * the index of the last element of {@code perm} (exclusive) to be * permuted. * @param stable * whether the sorting algorithm should be stable. */ public static void radixSortIndirect(final int[] perm, final int[] a, final int from, final int to, final boolean stable) { if (to - from < RADIXSORT_NO_REC) { insertionSortIndirect(perm, a, from, to); return; } final int maxLevel = DIGITS_PER_ELEMENT - 1; final int stackSize = ((1 << DIGIT_BITS) - 1) * (DIGITS_PER_ELEMENT - 1) + 1; int stackPos = 0; final int[] offsetStack = new int[stackSize]; final int[] lengthStack = new int[stackSize]; final int[] levelStack = new int[stackSize]; offsetStack[stackPos] = from; lengthStack[stackPos] = to - from; levelStack[stackPos++] = 0; final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; final int[] support = stable ? new int[perm.length] : null; while (stackPos > 0) { final int first = offsetStack[--stackPos]; final int length = lengthStack[stackPos]; final int level = levelStack[stackPos]; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the shift // that extract the // right byte from a // key // Count keys. for (int i = first + length; i-- != first;) count[((a[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = stable ? 0 : first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } if (stable) { for (int i = first + length; i-- != first;) support[--pos[((a[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]] = perm[i]; System.arraycopy(support, 0, perm, first, length); for (int i = 0, p = first; i <= lastUsed; i++) { if (level < maxLevel && count[i] > 1) { if (count[i] < RADIXSORT_NO_REC) insertionSortIndirect(perm, a, p, p + count[i]); else { offsetStack[stackPos] = p; lengthStack[stackPos] = count[i]; levelStack[stackPos++] = level + 1; } } p += count[i]; } java.util.Arrays.fill(count, 0); } else { final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = perm[i]; c = ((a[t]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { final int z = t; t = perm[d]; perm[d] = z; c = ((a[t]) >>> shift & DIGIT_MASK ^ signMask); } perm[i] = t; } if (level < maxLevel && count[c] > 1) { if (count[c] < RADIXSORT_NO_REC) insertionSortIndirect(perm, a, i, i + count[c]); else { offsetStack[stackPos] = i; lengthStack[stackPos] = count[c]; levelStack[stackPos++] = level + 1; } } } } } } /** * Sorts the specified range of an array using parallel indirect radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]}. * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. * @param stable * whether the sorting algorithm should be stable. */ public static void parallelRadixSortIndirect(final int perm[], final int[] a, final int from, final int to, final boolean stable) { if (to - from < PARALLEL_RADIXSORT_NO_FORK) { radixSortIndirect(perm, a, from, to, stable); return; } final int maxLevel = DIGITS_PER_ELEMENT - 1; final LinkedBlockingQueue queue = new LinkedBlockingQueue<>(); queue.add(new Segment(from, to - from, 0)); final AtomicInteger queueSize = new AtomicInteger(1); final int numberOfThreads = Runtime.getRuntime().availableProcessors(); final ExecutorService executorService = Executors.newFixedThreadPool(numberOfThreads, Executors.defaultThreadFactory()); final ExecutorCompletionService executorCompletionService = new ExecutorCompletionService<>( executorService); final int[] support = stable ? new int[perm.length] : null; for (int j = numberOfThreads; j-- != 0;) executorCompletionService.submit(() -> { final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; for (;;) { if (queueSize.get() == 0) for (int i = numberOfThreads; i-- != 0;) queue.add(POISON_PILL); final Segment segment = queue.take(); if (segment == POISON_PILL) return null; final int first = segment.offset; final int length = segment.length; final int level = segment.level; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the // shift // that // extract // the right // byte from // a key // Count keys. for (int i = first + length; i-- != first;) count[((a[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } if (stable) { for (int i = first + length; i-- != first;) support[--pos[((a[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]] = perm[i]; System.arraycopy(support, first, perm, first, length); for (int i = 0, p = first; i <= lastUsed; i++) { if (level < maxLevel && count[i] > 1) { if (count[i] < PARALLEL_RADIXSORT_NO_FORK) radixSortIndirect(perm, a, p, p + count[i], stable); else { queueSize.incrementAndGet(); queue.add(new Segment(p, count[i], level + 1)); } } p += count[i]; } java.util.Arrays.fill(count, 0); } else { final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = perm[i]; c = ((a[t]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { final int z = t; t = perm[d]; perm[d] = z; c = ((a[t]) >>> shift & DIGIT_MASK ^ signMask); } perm[i] = t; } if (level < maxLevel && count[c] > 1) { if (count[c] < PARALLEL_RADIXSORT_NO_FORK) radixSortIndirect(perm, a, i, i + count[c], stable); else { queueSize.incrementAndGet(); queue.add(new Segment(i, count[c], level + 1)); } } } } queueSize.decrementAndGet(); } }); Throwable problem = null; for (int i = numberOfThreads; i-- != 0;) try { executorCompletionService.take().get(); } catch (Exception e) { problem = e.getCause(); // We keep only the last one. They will be logged anyway. } executorService.shutdown(); if (problem != null) throw (problem instanceof RuntimeException) ? (RuntimeException) problem : new RuntimeException(problem); } /** * Sorts the specified array using parallel indirect radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]}. * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param stable * whether the sorting algorithm should be stable. */ public static void parallelRadixSortIndirect(final int perm[], final int[] a, final boolean stable) { parallelRadixSortIndirect(perm, a, 0, a.length, stable); } /** * Sorts the specified pair of arrays lexicographically using radix sort. *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code a[i] < a[i + 1]} or {@code a[i] == a[i + 1]} and * {@code b[i] ≤ b[i + 1]}. * * @param a * the first array to be sorted. * @param b * the second array to be sorted. */ public static void radixSort(final int[] a, final int[] b) { ensureSameLength(a, b); radixSort(a, b, 0, a.length); } /** * Sorts the specified range of elements of two arrays using radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code a[i] < a[i + 1]} or {@code a[i] == a[i + 1]} and * {@code b[i] ≤ b[i + 1]}. * * @param a * the first array to be sorted. * @param b * the second array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void radixSort(final int[] a, final int[] b, final int from, final int to) { if (to - from < RADIXSORT_NO_REC) { selectionSort(a, b, from, to); return; } final int layers = 2; final int maxLevel = DIGITS_PER_ELEMENT * layers - 1; final int stackSize = ((1 << DIGIT_BITS) - 1) * (layers * DIGITS_PER_ELEMENT - 1) + 1; int stackPos = 0; final int[] offsetStack = new int[stackSize]; final int[] lengthStack = new int[stackSize]; final int[] levelStack = new int[stackSize]; offsetStack[stackPos] = from; lengthStack[stackPos] = to - from; levelStack[stackPos++] = 0; final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; while (stackPos > 0) { final int first = offsetStack[--stackPos]; final int length = lengthStack[stackPos]; final int level = levelStack[stackPos]; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int[] k = level < DIGITS_PER_ELEMENT ? a : b; // This is the key array final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the shift // that extract the // right byte from a // key // Count keys. for (int i = first + length; i-- != first;) count[((k[i]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = a[i]; int u = b[i]; c = ((k[i]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { c = ((k[d]) >>> shift & DIGIT_MASK ^ signMask); int z = t; t = a[d]; a[d] = z; z = u; u = b[d]; b[d] = z; } a[i] = t; b[i] = u; } if (level < maxLevel && count[c] > 1) { if (count[c] < RADIXSORT_NO_REC) selectionSort(a, b, i, i + count[c]); else { offsetStack[stackPos] = i; lengthStack[stackPos] = count[c]; levelStack[stackPos++] = level + 1; } } } } } /** * Sorts the specified range of elements of two arrays using a parallel radix * sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code a[i] < a[i + 1]} or {@code a[i] == a[i + 1]} and * {@code b[i] ≤ b[i + 1]}. * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param a * the first array to be sorted. * @param b * the second array to be sorted. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void parallelRadixSort(final int[] a, final int[] b, final int from, final int to) { if (to - from < PARALLEL_RADIXSORT_NO_FORK) { quickSort(a, b, from, to); return; } final int layers = 2; if (a.length != b.length) throw new IllegalArgumentException("Array size mismatch."); final int maxLevel = DIGITS_PER_ELEMENT * layers - 1; final LinkedBlockingQueue queue = new LinkedBlockingQueue<>(); queue.add(new Segment(from, to - from, 0)); final AtomicInteger queueSize = new AtomicInteger(1); final int numberOfThreads = Runtime.getRuntime().availableProcessors(); final ExecutorService executorService = Executors.newFixedThreadPool(numberOfThreads, Executors.defaultThreadFactory()); final ExecutorCompletionService executorCompletionService = new ExecutorCompletionService<>( executorService); for (int j = numberOfThreads; j-- != 0;) executorCompletionService.submit(() -> { final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; for (;;) { if (queueSize.get() == 0) for (int i = numberOfThreads; i-- != 0;) queue.add(POISON_PILL); final Segment segment = queue.take(); if (segment == POISON_PILL) return null; final int first = segment.offset; final int length = segment.length; final int level = segment.level; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int[] k = level < DIGITS_PER_ELEMENT ? a : b; // This is the key array final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // Count keys. for (int i = first + length; i-- != first;) count[((k[i]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } final int end = first + length - count[lastUsed]; for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = a[i]; int u = b[i]; c = ((k[i]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { c = ((k[d]) >>> shift & DIGIT_MASK ^ signMask); final int z = t; final int w = u; t = a[d]; u = b[d]; a[d] = z; b[d] = w; } a[i] = t; b[i] = u; } if (level < maxLevel && count[c] > 1) { if (count[c] < PARALLEL_RADIXSORT_NO_FORK) quickSort(a, b, i, i + count[c]); else { queueSize.incrementAndGet(); queue.add(new Segment(i, count[c], level + 1)); } } } queueSize.decrementAndGet(); } }); Throwable problem = null; for (int i = numberOfThreads; i-- != 0;) try { executorCompletionService.take().get(); } catch (Exception e) { problem = e.getCause(); // We keep only the last one. They will be logged anyway. } executorService.shutdown(); if (problem != null) throw (problem instanceof RuntimeException) ? (RuntimeException) problem : new RuntimeException(problem); } /** * Sorts two arrays using a parallel radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the arguments. * Pairs of elements in the same position in the two provided arrays will be * considered a single key, and permuted accordingly. In the end, either * {@code a[i] < a[i + 1]} or {@code a[i] == a[i + 1]} and * {@code b[i] ≤ b[i + 1]}. * *

* This implementation uses a pool of {@link Runtime#availableProcessors()} * threads. * * @param a * the first array to be sorted. * @param b * the second array to be sorted. */ public static void parallelRadixSort(final int[] a, final int[] b) { ensureSameLength(a, b); parallelRadixSort(a, b, 0, a.length); } private static void insertionSortIndirect(final int[] perm, final int[] a, final int[] b, final int from, final int to) { for (int i = from; ++i < to;) { int t = perm[i]; int j = i; for (int u = perm[j - 1]; ((a[t]) < (a[u])) || ((a[t]) == (a[u])) && ((b[t]) < (b[u])); u = perm[--j - 1]) { perm[j] = u; if (from == j - 1) { --j; break; } } perm[j] = t; } } /** * Sorts the specified pair of arrays lexicographically using indirect radix * sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]} or * {@code a[perm[i]] == a[perm[i + 1]]} and * {@code b[perm[i]] ≤ b[perm[i + 1]]}. * *

* This implementation will allocate, in the stable case, a further support * array as large as {@code perm} (note that the stable version is slightly * faster). * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param b * the second array to be sorted. * @param stable * whether the sorting algorithm should be stable. */ public static void radixSortIndirect(final int[] perm, final int[] a, final int[] b, final boolean stable) { ensureSameLength(a, b); radixSortIndirect(perm, a, b, 0, a.length, stable); } /** * Sorts the specified pair of arrays lexicographically using indirect radix * sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implement an indirect sort. The elements of {@code perm} * (which must be exactly the numbers in the interval {@code [0..perm.length)}) * will be permuted so that {@code a[perm[i]] ≤ a[perm[i + 1]]} or * {@code a[perm[i]] == a[perm[i + 1]]} and * {@code b[perm[i]] ≤ b[perm[i + 1]]}. * *

* This implementation will allocate, in the stable case, a further support * array as large as {@code perm} (note that the stable version is slightly * faster). * * @param perm * a permutation array indexing {@code a}. * @param a * the array to be sorted. * @param b * the second array to be sorted. * @param from * the index of the first element of {@code perm} (inclusive) to be * permuted. * @param to * the index of the last element of {@code perm} (exclusive) to be * permuted. * @param stable * whether the sorting algorithm should be stable. */ public static void radixSortIndirect(final int[] perm, final int[] a, final int[] b, final int from, final int to, final boolean stable) { if (to - from < RADIXSORT_NO_REC) { insertionSortIndirect(perm, a, b, from, to); return; } final int layers = 2; final int maxLevel = DIGITS_PER_ELEMENT * layers - 1; final int stackSize = ((1 << DIGIT_BITS) - 1) * (layers * DIGITS_PER_ELEMENT - 1) + 1; int stackPos = 0; final int[] offsetStack = new int[stackSize]; final int[] lengthStack = new int[stackSize]; final int[] levelStack = new int[stackSize]; offsetStack[stackPos] = from; lengthStack[stackPos] = to - from; levelStack[stackPos++] = 0; final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; final int[] support = stable ? new int[perm.length] : null; while (stackPos > 0) { final int first = offsetStack[--stackPos]; final int length = lengthStack[stackPos]; final int level = levelStack[stackPos]; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int[] k = level < DIGITS_PER_ELEMENT ? a : b; // This is the key array final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the shift // that extract the // right byte from a // key // Count keys. for (int i = first + length; i-- != first;) count[((k[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = stable ? 0 : first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } if (stable) { for (int i = first + length; i-- != first;) support[--pos[((k[perm[i]]) >>> shift & DIGIT_MASK ^ signMask)]] = perm[i]; System.arraycopy(support, 0, perm, first, length); for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (level < maxLevel && count[i] > 1) { if (count[i] < RADIXSORT_NO_REC) insertionSortIndirect(perm, a, b, p, p + count[i]); else { offsetStack[stackPos] = p; lengthStack[stackPos] = count[i]; levelStack[stackPos++] = level + 1; } } p += count[i]; } java.util.Arrays.fill(count, 0); } else { final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { int t = perm[i]; c = ((k[t]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { final int z = t; t = perm[d]; perm[d] = z; c = ((k[t]) >>> shift & DIGIT_MASK ^ signMask); } perm[i] = t; } if (level < maxLevel && count[c] > 1) { if (count[c] < RADIXSORT_NO_REC) insertionSortIndirect(perm, a, b, i, i + count[c]); else { offsetStack[stackPos] = i; lengthStack[stackPos] = count[c]; levelStack[stackPos++] = level + 1; } } } } } } private static void selectionSort(final int[][] a, final int from, final int to, final int level) { final int layers = a.length; final int firstLayer = level / DIGITS_PER_ELEMENT; for (int i = from; i < to - 1; i++) { int m = i; for (int j = i + 1; j < to; j++) { for (int p = firstLayer; p < layers; p++) { if (a[p][j] < a[p][m]) { m = j; break; } else if (a[p][j] > a[p][m]) break; } } if (m != i) { for (int p = layers; p-- != 0;) { final int u = a[p][i]; a[p][i] = a[p][m]; a[p][m] = u; } } } } /** * Sorts the specified array of arrays lexicographically using radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the provided * arrays. Tuples of elements in the same position will be considered a single * key, and permuted accordingly. * * @param a * an array containing arrays of equal length to be sorted * lexicographically in parallel. */ public static void radixSort(final int[][] a) { radixSort(a, 0, a[0].length); } /** * Sorts the specified array of arrays lexicographically using radix sort. * *

* The sorting algorithm is a tuned radix sort adapted from Peter M. McIlroy, * Keith Bostic and M. Douglas McIlroy, “Engineering radix sort”, * Computing Systems, 6(1), pages 5−27 (1993). * *

* This method implements a lexicographical sorting of the provided * arrays. Tuples of elements in the same position will be considered a single * key, and permuted accordingly. * * @param a * an array containing arrays of equal length to be sorted * lexicographically in parallel. * @param from * the index of the first element (inclusive) to be sorted. * @param to * the index of the last element (exclusive) to be sorted. */ public static void radixSort(final int[][] a, final int from, final int to) { if (to - from < RADIXSORT_NO_REC) { selectionSort(a, from, to, 0); return; } final int layers = a.length; final int maxLevel = DIGITS_PER_ELEMENT * layers - 1; for (int p = layers, l = a[0].length; p-- != 0;) if (a[p].length != l) throw new IllegalArgumentException( "The array of index " + p + " has not the same length of the array of index 0."); final int stackSize = ((1 << DIGIT_BITS) - 1) * (layers * DIGITS_PER_ELEMENT - 1) + 1; int stackPos = 0; final int[] offsetStack = new int[stackSize]; final int[] lengthStack = new int[stackSize]; final int[] levelStack = new int[stackSize]; offsetStack[stackPos] = from; lengthStack[stackPos] = to - from; levelStack[stackPos++] = 0; final int[] count = new int[1 << DIGIT_BITS]; final int[] pos = new int[1 << DIGIT_BITS]; final int[] t = new int[layers]; while (stackPos > 0) { final int first = offsetStack[--stackPos]; final int length = lengthStack[stackPos]; final int level = levelStack[stackPos]; final int signMask = level % DIGITS_PER_ELEMENT == 0 ? 1 << DIGIT_BITS - 1 : 0; final int[] k = a[level / DIGITS_PER_ELEMENT]; // This is the key array final int shift = (DIGITS_PER_ELEMENT - 1 - level % DIGITS_PER_ELEMENT) * DIGIT_BITS; // This is the shift // that extract the // right byte from a // key // Count keys. for (int i = first + length; i-- != first;) count[((k[i]) >>> shift & DIGIT_MASK ^ signMask)]++; // Compute cumulative distribution int lastUsed = -1; for (int i = 0, p = first; i < 1 << DIGIT_BITS; i++) { if (count[i] != 0) lastUsed = i; pos[i] = (p += count[i]); } final int end = first + length - count[lastUsed]; // i moves through the start of each block for (int i = first, c = -1, d; i <= end; i += count[c], count[c] = 0) { for (int p = layers; p-- != 0;) t[p] = a[p][i]; c = ((k[i]) >>> shift & DIGIT_MASK ^ signMask); if (i < end) { // When all slots are OK, the last slot is necessarily OK. while ((d = --pos[c]) > i) { c = ((k[d]) >>> shift & DIGIT_MASK ^ signMask); for (int p = layers; p-- != 0;) { final int u = t[p]; t[p] = a[p][d]; a[p][d] = u; } } for (int p = layers; p-- != 0;) a[p][i] = t[p]; } if (level < maxLevel && count[c] > 1) { if (count[c] < RADIXSORT_NO_REC) selectionSort(a, i, i + count[c], level + 1); else { offsetStack[stackPos] = i; lengthStack[stackPos] = count[c]; levelStack[stackPos++] = level + 1; } } } } } /** * Shuffles the specified array fragment using the specified pseudorandom number * generator. * * @param a * the array to be shuffled. * @param from * the index of the first element (inclusive) to be shuffled. * @param to * the index of the last element (exclusive) to be shuffled. * @param random * a pseudorandom number generator. * @return {@code a}. */ public static int[] shuffle(final int[] a, final int from, final int to, final Random random) { for (int i = to - from; i-- != 0;) { final int p = random.nextInt(i + 1); final int t = a[from + i]; a[from + i] = a[from + p]; a[from + p] = t; } return a; } /** * Shuffles the specified array using the specified pseudorandom number * generator. * * @param a * the array to be shuffled. * @param random * a pseudorandom number generator. * @return {@code a}. */ public static int[] shuffle(final int[] a, final Random random) { for (int i = a.length; i-- != 0;) { final int p = random.nextInt(i + 1); final int t = a[i]; a[i] = a[p]; a[p] = t; } return a; } /** * Reverses the order of the elements in the specified array. * * @param a * the array to be reversed. * @return {@code a}. */ public static int[] reverse(final int[] a) { final int length = a.length; for (int i = length / 2; i-- != 0;) { final int t = a[length - i - 1]; a[length - i - 1] = a[i]; a[i] = t; } return a; } /** * Reverses the order of the elements in the specified array fragment. * * @param a * the array to be reversed. * @param from * the index of the first element (inclusive) to be reversed. * @param to * the index of the last element (exclusive) to be reversed. * @return {@code a}. */ public static int[] reverse(final int[] a, final int from, final int to) { final int length = to - from; for (int i = length / 2; i-- != 0;) { final int t = a[from + length - i - 1]; a[from + length - i - 1] = a[from + i]; a[from + i] = t; } return a; } /** A type-specific content-based hash strategy for arrays. */ private static final class ArrayHashStrategy implements Hash.Strategy, java.io.Serializable { private static final long serialVersionUID = -7046029254386353129L; @Override public int hashCode(final int[] o) { return java.util.Arrays.hashCode(o); } @Override public boolean equals(final int[] a, final int[] b) { return java.util.Arrays.equals(a, b); } } /** * A type-specific content-based hash strategy for arrays. * *

* This hash strategy may be used in custom hash collections whenever keys are * arrays, and they must be considered equal by content. This strategy will * handle {@code null} correctly, and it is serializable. */ public static final Hash.Strategy HASH_STRATEGY = new ArrayHashStrategy(); }





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