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Added StockBuySell Java implementation #940

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135 changes: 135 additions & 0 deletions Dynamic Programming/StockBuySell.java
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Original file line number Diff line number Diff line change
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package DynamicProgramming;

import java.util.Deque;
import java.util.LinkedList;


public class StockBuySellKTransactions {

public int maxProfitLinearSpace(int k, int[] prices) {
if (k == 0 || prices.length == 0) {
return 0;
}

if (k >= prices.length) {
return allTimeProfit(prices);
}
int[] T = new int[prices.length];
int[] prev = new int[prices.length];
for (int i = 1; i <= k; i++) {
int maxDiff = -prices[0];
for (int j = 1; j < prices.length; j++) {
T[j] = Math.max(T[j - 1], maxDiff + prices[j]);
maxDiff = Math.max(maxDiff, prev[j] - prices[j]);
}
for (int j = 1; j < prices.length; j++) {
prev[j] = T[j];
}
}
return T[T.length - 1];
}

public int allTimeProfit(int arr[]){
int profit = 0;
int localMin = arr[0];
for(int i=1; i < arr.length;i++){
if(arr[i-1] >= arr[i]){
localMin = arr[i];
}else{
profit += arr[i] - localMin;
localMin = arr[i];
}

}
return profit;
}

/**
* This is faster method which does optimization on slower method
* Time complexity here is O(K * number of days)
*
* Formula is
* T[i][j] = max(T[i][j-1], prices[j] + maxDiff)
* maxDiff = max(maxDiff, T[i-1][j] - prices[j])
*/
public int maxProfit(int prices[], int K) {
if (K == 0 || prices.length == 0) {
return 0;
}
int T[][] = new int[K+1][prices.length];

for (int i = 1; i < T.length; i++) {
int maxDiff = -prices[0];
for (int j = 1; j < T[0].length; j++) {
T[i][j] = Math.max(T[i][j-1], prices[j] + maxDiff);
maxDiff = Math.max(maxDiff, T[i-1][j] - prices[j]);
}
}
printActualSolution(T, prices);
return T[K][prices.length-1];
}

/**
* This is slow method but easier to understand.
* Time complexity is O(k * number of days ^ 2)
* T[i][j] = max(T[i][j-1], max(prices[j] - prices[m] + T[i-1][m])) where m is 0...j-1
*/
public int maxProfitSlowSolution(int prices[], int K) {
if (K == 0 || prices.length == 0) {
return 0;
}
int T[][] = new int[K+1][prices.length];

for (int i = 1; i < T.length; i++) {
for (int j = 1; j < T[0].length; j++) {
int maxVal = 0;
for (int m = 0; m < j; m++) {
maxVal = Math.max(maxVal, prices[j] - prices[m] + T[i-1][m]);
}
T[i][j] = Math.max(T[i][j-1], maxVal);
}
}
printActualSolution(T, prices);
return T[K][prices.length - 1];
}

public void printActualSolution(int T[][], int prices[]) {
int i = T.length - 1;
int j = T[0].length - 1;

Deque<Integer> stack = new LinkedList<>();
while(true) {
if(i == 0 || j == 0) {
break;
}
if (T[i][j] == T[i][j-1]) {
j = j - 1;
} else {
stack.addFirst(j);
int maxDiff = T[i][j] - prices[j];
for (int k = j-1; k >= 0; k--) {
if (T[i-1][k] - prices[k] == maxDiff) {
i = i - 1;
j = k;
stack.addFirst(j);
break;
}
}
}
}

while(!stack.isEmpty()) {
System.out.println("Buy at price " + prices[stack.pollFirst()]);
System.out.println("Sell at price " + prices[stack.pollFirst()]);
}

}

public static void main(String args[]) {
StockBuySellKTransactions sbt = new StockBuySellKTransactions();
int prices[] = {2, 5, 7, 1, 4, 3, 1, 3};

System.out.println("Max profit fast solution " + sbt.maxProfit(prices, 3));
System.out.println("Max profit slow solution " + sbt.maxProfitSlowSolution(prices, 3));
}
}