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LongestIncreasingSubsequence.java
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LongestIncreasingSubsequence.java
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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;
}
}