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CoinChange.java
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CoinChange.java
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/**
* The coin change problem is an unbounded knapsack problem variant. The problem asks you to find
* the minimum number of coins required for a certain amount of change given the coin denominations.
* You may use each coin denomination as many times as you please.
*
* <p>Tested against: https://leetcode.com/problems/coin-change
*
* <p>Run locally:
*
* <p>./gradlew run -Palgorithm=dp.CoinChange
*
* @author William Fiset, william.alexandre.fiset@gmail.com
*/
package com.williamfiset.algorithms.dp;
import java.util.ArrayList;
import java.util.List;
import java.util.Optional;
public class CoinChange {
public static class Solution {
// Contains the minimum number of coins to make a certain amount, if a solution exists.
Optional<Integer> minCoins = Optional.empty();
// The coins selected as part of the optimal solution.
List<Integer> selectedCoins = new ArrayList<Integer>();
}
// TODO(william): setting an explicit infinity could lead to a wrong answer for
// very large values. Prefer to use null instead.
private static final int INF = Integer.MAX_VALUE / 2;
public static Solution coinChange(int[] coins, final int n) {
if (coins == null) throw new IllegalArgumentException("Coins array is null");
if (coins.length == 0) throw new IllegalArgumentException("No coin values :/");
for (int coin : coins) {
if (coin <= 0) {
throw new IllegalArgumentException("Coin with value `" + coin + "` is not allowed.");
}
}
final int m = coins.length;
// Initialize table and set first row to be infinity
int[][] dp = new int[m + 1][n + 1];
java.util.Arrays.fill(dp[0], INF);
dp[1][0] = 0;
// Iterate through all the coins
for (int i = 1; i <= m; i++) {
int coinValue = coins[i - 1];
for (int j = 1; j <= n; j++) {
// Consider not selecting this coin
dp[i][j] = dp[i - 1][j];
// Try selecting this coin if it's better
if (j - coinValue >= 0 && dp[i][j - coinValue] + 1 < dp[i][j]) {
dp[i][j] = dp[i][j - coinValue] + 1;
}
}
}
// p(dp);
Solution solution = new Solution();
if (dp[m][n] != INF) {
solution.minCoins = Optional.of(dp[m][n]);
} else {
return solution;
}
for (int change = n, coinIndex = m; coinIndex > 0; ) {
int coinValue = coins[coinIndex - 1];
boolean canSelectCoin = change - coinValue >= 0;
if (canSelectCoin && dp[coinIndex][change - coinValue] < dp[coinIndex][change]) {
solution.selectedCoins.add(coinValue);
change -= coinValue;
} else {
coinIndex--;
}
}
return solution;
}
public static Solution coinChangeSpaceEfficient(int[] coins, int n) {
if (coins == null) throw new IllegalArgumentException("Coins array is null");
// Initialize table and set everything to infinity except first cell
int[] dp = new int[n + 1];
java.util.Arrays.fill(dp, INF);
dp[0] = 0;
for (int i = 1; i <= n; i++) {
for (int coin : coins) {
if (i - coin < 0) {
continue;
}
if (dp[i - coin] + 1 < dp[i]) {
dp[i] = dp[i - coin] + 1;
}
}
}
Solution solution = new Solution();
if (dp[n] != INF) {
solution.minCoins = Optional.of(dp[n]);
} else {
return solution;
}
for (int i = n; i > 0; ) {
int selectedCoinValue = INF;
int cellWithFewestCoins = dp[i];
for (int coin : coins) {
if (i - coin < 0) {
continue;
}
if (dp[i - coin] < cellWithFewestCoins) {
cellWithFewestCoins = dp[i - coin];
selectedCoinValue = coin;
}
}
solution.selectedCoins.add(selectedCoinValue);
i -= selectedCoinValue;
}
// Return the minimum number of coins needed
return solution;
}
// The recursive approach has the advantage that it does not have to visit
// all possible states like the tabular approach does. This can speedup
// things especially if the coin denominations are large.
public static int coinChangeRecursive(int[] coins, int n) {
if (coins == null) throw new IllegalArgumentException("Coins array is null");
if (n < 0) return -1;
int[] dp = new int[n + 1];
return coinChangeRecursive(n, coins, dp);
}
// Private helper method to actually go the recursion
private static int coinChangeRecursive(int n, int[] coins, int[] dp) {
if (n < 0) return -1;
if (n == 0) return 0;
if (dp[n] != 0) return dp[n];
int minCoins = INF;
for (int coinValue : coins) {
int value = coinChangeRecursive(n - coinValue, coins, dp);
if (value != -1 && value < minCoins) minCoins = value + 1;
}
// If we weren't able to find some coins to make our
// amount then cache -1 as the answer.
return dp[n] = (minCoins == INF) ? -1 : minCoins;
}
// DP table print function. Used for debugging.
private static void p(int[][] dp) {
for (int[] r : dp) {
for (int v : r) {
System.out.printf("%4d, ", v == INF ? -1 : v);
}
System.out.println();
}
}
private static void p(int[] dp) {
for (int v : dp) {
System.out.printf("%4d, ", v == INF ? -1 : v);
}
System.out.println();
}
public static void main(String[] args) {
// example1();
// example2();
// example3();
example4();
}
private static void example4() {
int n = 11;
int[] coins = {2, 4, 1};
// System.out.println(coinChange(coins, n).minCoins);
System.out.println(coinChangeSpaceEfficient(coins, n));
// System.out.println(coinChangeRecursive(coins, n));
// System.out.println(coinChange(coins, n).selectedCoins);
}
private static void example1() {
int[] coins = {2, 6, 1};
System.out.println(coinChange(coins, 17).minCoins);
System.out.println(coinChange(coins, 17).selectedCoins);
System.out.println(coinChangeSpaceEfficient(coins, 17));
System.out.println(coinChangeRecursive(coins, 17));
}
private static void example2() {
int[] coins = {2, 3, 5};
System.out.println(coinChange(coins, 12).minCoins);
System.out.println(coinChange(coins, 12).selectedCoins);
System.out.println(coinChangeSpaceEfficient(coins, 12));
System.out.println(coinChangeRecursive(coins, 12));
}
private static void example3() {
int[] coins = {3, 4, 7};
System.out.println(coinChange(coins, 17).minCoins);
System.out.println(coinChange(coins, 17).selectedCoins);
System.out.println(coinChangeSpaceEfficient(coins, 17));
System.out.println(coinChangeRecursive(coins, 17));
}
}