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68 lines
2.6 KiB
Java
68 lines
2.6 KiB
Java
package com.thealgorithms.dynamicprogramming;
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/**
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* Find the number of subsets present in the given array with a sum equal to target.
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* Based on Solution discussed on
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* StackOverflow(https://stackoverflow.com/questions/22891076/count-number-of-subsets-with-sum-equal-to-k)
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* @author Samrat Podder(https://github.com/samratpodder)
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*/
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public class SubsetCount {
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/**
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* Dynamic Programming Implementation.
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* Method to find out the number of subsets present in the given array with a sum equal to
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* target. Time Complexity is O(n*target) and Space Complexity is O(n*target)
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* @param arr is the input array on which subsets are to searched
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* @param target is the sum of each element of the subset taken together
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*
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*/
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public int getCount(int[] arr, int target) {
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/**
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* Base Cases - If target becomes zero, we have reached the required sum for the subset
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* If we reach the end of the array arr then, either if target==arr[end], then we add one to
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* the final count Otherwise we add 0 to the final count
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*/
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int n = arr.length;
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int[][] dp = new int[n][target + 1];
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for (int i = 0; i < n; i++) {
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dp[i][0] = 1;
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}
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if (arr[0] <= target) dp[0][arr[0]] = 1;
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for (int t = 1; t <= target; t++) {
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for (int idx = 1; idx < n; idx++) {
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int notpick = dp[idx - 1][t];
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int pick = 0;
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if (arr[idx] <= t) pick += dp[idx - 1][target - t];
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dp[idx][target] = pick + notpick;
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}
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}
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return dp[n - 1][target];
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}
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/**
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* This Method is a Space Optimized version of the getCount(int[], int) method and solves the
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* same problem This approach is a bit better in terms of Space Used Time Complexity is
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* O(n*target) and Space Complexity is O(target)
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* @param arr is the input array on which subsets are to searched
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* @param target is the sum of each element of the subset taken together
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*/
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public int getCountSO(int[] arr, int target) {
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int n = arr.length;
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int[] prev = new int[target + 1];
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prev[0] = 1;
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if (arr[0] <= target) prev[arr[0]] = 1;
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for (int ind = 1; ind < n; ind++) {
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int[] cur = new int[target + 1];
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cur[0] = 1;
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for (int t = 1; t <= target; t++) {
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int notTaken = prev[t];
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int taken = 0;
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if (arr[ind] <= t) taken = prev[t - arr[ind]];
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cur[t] = notTaken + taken;
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}
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prev = cur;
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}
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return prev[target];
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}
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}
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