package com.thealgorithms.dynamicprogramming; /** * @author Afrizal Fikri (https://github.com/icalF) */ public final class LongestIncreasingSubsequence { private LongestIncreasingSubsequence() { } private static int upperBound(int[] ar, int l, int r, int key) { while (l < r - 1) { int m = (l + r) >>> 1; if (ar[m] >= key) { r = m; } else { l = m; } } return r; } public static int lis(int[] array) { int len = array.length; if (len == 0) { return 0; } int[] tail = new int[len]; // always points empty slot in tail int length = 1; tail[0] = array[0]; for (int i = 1; i < len; i++) { // new smallest value if (array[i] < tail[0]) { tail[0] = array[i]; } // array[i] extends largest subsequence else if (array[i] > tail[length - 1]) { tail[length++] = array[i]; } // array[i] will become end candidate of an existing subsequence or // Throw away larger elements in all LIS, to make room for upcoming grater elements than // array[i] // (and also, array[i] would have already appeared in one of LIS, identify the location // and replace it) else { tail[upperBound(tail, -1, length - 1, array[i])] = array[i]; } } return length; } /** * @author Alon Firestein (https://github.com/alonfirestein) */ // A function for finding the length of the LIS algorithm in O(nlogn) complexity. public static int findLISLen(int[] a) { final int size = a.length; if (size == 0) { return 0; } int[] arr = new int[size]; arr[0] = a[0]; int lis = 1; for (int i = 1; i < size; i++) { int index = binarySearchBetween(arr, lis - 1, a[i]); arr[index] = a[i]; if (index == lis) { lis++; } } return lis; } // O(logn) private static int binarySearchBetween(int[] t, int end, int key) { int left = 0; int right = end; if (key < t[0]) { return 0; } if (key > t[end]) { return end + 1; } while (left < right - 1) { final int middle = (left + right) >>> 1; if (t[middle] < key) { left = middle; } else { right = middle; } } return right; } }