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Core sketch algorithms used alone and by other Java repositories in the DataSketches library.
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.datasketches.thetacommon;
/**
* QuickSelect algorithm improved from Sedgewick. Gets the kth order value
* (1-based or 0-based) from the array.
* Warning! This changes the ordering of elements in the given array!
* Also see:
* blog.teamleadnet.com/2012/07/quick-select-algorithm-find-kth-element.html
* See QuickSelectTest for examples and testNG tests.
*
* @author Lee Rhodes
*/
public final class QuickSelect {
private QuickSelect() {}
/**
* Gets the 0-based kth order statistic from the array. Warning! This changes the ordering
* of elements in the given array!
*
* @param arr The array to be re-arranged.
* @param lo The lowest 0-based index to be considered.
* @param hi The highest 0-based index to be considered.
* @param pivot The 0-based index of the value to pivot on.
* @return The value of the smallest (n)th element where n is 0-based.
*/
public static long select(final long[] arr, int lo, int hi, final int pivot) {
while (hi > lo) {
final int j = partition(arr, lo, hi);
if (j == pivot) {
return arr[pivot];
}
if (j > pivot) {
hi = j - 1;
}
else {
lo = j + 1;
}
}
return arr[pivot];
}
/**
* Gets the 1-based kth order statistic from the array including any zero values in the
* array. Warning! This changes the ordering of elements in the given array!
*
* @param arr The hash array.
* @param pivot The 1-based index of the value that is chosen as the pivot for the array.
* After the operation all values below this 1-based index will be less than this value
* and all values above this index will be greater. The 0-based index of the pivot will be
* pivot-1.
* @return The value of the smallest (N)th element including zeros, where N is 1-based.
*/
public static long selectIncludingZeros(final long[] arr, final int pivot) {
final int arrSize = arr.length;
final int adj = pivot - 1;
return select(arr, 0, arrSize - 1, adj);
}
/**
* Gets the 1-based kth order statistic from the array excluding any zero values in the
* array. Warning! This changes the ordering of elements in the given array!
*
* @param arr The hash array.
* @param nonZeros The number of non-zero values in the array.
* @param pivot The 1-based index of the value that is chosen as the pivot for the array.
* After the operation all values below this 1-based index will be less than this value
* and all values above this index will be greater. The 0-based index of the pivot will be
* pivot+arr.length-nonZeros-1.
* @return The value of the smallest (N)th element excluding zeros, where N is 1-based.
*/
public static long selectExcludingZeros(final long[] arr, final int nonZeros, final int pivot) {
if (pivot > nonZeros) {
return 0L;
}
final int arrSize = arr.length;
final int zeros = arrSize - nonZeros;
final int adjK = (pivot + zeros) - 1;
return select(arr, 0, arrSize - 1, adjK);
}
/**
* Partition arr[] into arr[lo .. i-1], arr[i], arr[i+1,hi]
*
* @param arr The given array to partition
* @param lo the low index
* @param hi the high index
* @return the next partition value. Ultimately, the desired pivot.
*/
private static int partition(final long[] arr, final int lo, final int hi) {
int i = lo, j = hi + 1; //left and right scan indices
final long v = arr[lo]; //partitioning item value
while (true) {
//Scan right, scan left, check for scan complete, and exchange
while (arr[ ++i] < v) {
if (i == hi) {
break;
}
}
while (v < arr[ --j]) {
if (j == lo) {
break;
}
}
if (i >= j) {
break;
}
final long x = arr[i];
arr[i] = arr[j];
arr[j] = x;
}
//put v=arr[j] into position with a[lo .. j-1] <= a[j] <= a[j+1 .. hi]
final long x = arr[lo];
arr[lo] = arr[j];
arr[j] = x;
return j;
}
//For double arrays
/**
* Gets the 0-based kth order statistic from the array. Warning! This changes the ordering
* of elements in the given array!
*
* @param arr The array to be re-arranged.
* @param lo The lowest 0-based index to be considered.
* @param hi The highest 0-based index to be considered.
* @param pivot The 0-based smallest value to pivot on.
* @return The value of the smallest (n)th element where n is 0-based.
*/
public static double select(final double[] arr, int lo, int hi, final int pivot) {
while (hi > lo) {
final int j = partition(arr, lo, hi);
if (j == pivot) {
return arr[pivot];
}
if (j > pivot) {
hi = j - 1;
}
else {
lo = j + 1;
}
}
return arr[pivot];
}
/**
* Gets the 1-based kth order statistic from the array including any zero values in the
* array. Warning! This changes the ordering of elements in the given array!
*
* @param arr The hash array.
* @param pivot The 1-based index of the value that is chosen as the pivot for the array.
* After the operation all values below this 1-based index will be less than this value
* and all values above this index will be greater. The 0-based index of the pivot will be
* pivot-1.
* @return The value of the smallest (N)th element including zeros, where N is 1-based.
*/
public static double selectIncludingZeros(final double[] arr, final int pivot) {
final int arrSize = arr.length;
final int adj = pivot - 1;
return select(arr, 0, arrSize - 1, adj);
}
/**
* Gets the 1-based kth order statistic from the array excluding any zero values in the
* array. Warning! This changes the ordering of elements in the given array!
*
* @param arr The hash array.
* @param nonZeros The number of non-zero values in the array.
* @param pivot The 1-based index of the value that is chosen as the pivot for the array.
* After the operation all values below this 1-based index will be less than this value
* and all values above this index will be greater. The 0-based index of the pivot will be
* pivot+arr.length-nonZeros-1.
* @return The value of the smallest (N)th element excluding zeros, where N is 1-based.
*/
public static double selectExcludingZeros(final double[] arr, final int nonZeros, final int pivot) {
if (pivot > nonZeros) {
return 0L;
}
final int arrSize = arr.length;
final int zeros = arrSize - nonZeros;
final int adjK = (pivot + zeros) - 1;
return select(arr, 0, arrSize - 1, adjK);
}
/**
* Partition arr[] into arr[lo .. i-1], arr[i], arr[i+1,hi]
*
* @param arr The given array to partition
* @param lo the low index
* @param hi the high index
* @return the next partition value. Ultimately, the desired pivot.
*/
private static int partition(final double[] arr, final int lo, final int hi) {
int i = lo, j = hi + 1; //left and right scan indices
final double v = arr[lo]; //partitioning item value
while (true) {
//Scan right, scan left, check for scan complete, and exchange
while (arr[ ++i] < v) {
if (i == hi) {
break;
}
}
while (v < arr[ --j]) {
if (j == lo) {
break;
}
}
if (i >= j) {
break;
}
final double x = arr[i];
arr[i] = arr[j];
arr[j] = x;
}
//put v=arr[j] into position with a[lo .. j-1] <= a[j] <= a[j+1 .. hi]
final double x = arr[lo];
arr[lo] = arr[j];
arr[j] = x;
return j;
}
}
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