So the question is
You are given a 0-indexed integer array nums and an integer k.
You are initially standing at index 0. In one move, you can jump at most k steps forward without going outside the boundaries of the array. That is, you can jump from index i to any index in the range [i + 1, min(n - 1, i + k)] inclusive.
You want to reach the last index of the array (index n - 1). Your score is the sum of all nums[j] for each index j you visited in the array.
Return the maximum score you can get.
Example 1:
Input: nums = [1,-1,-2,4,-7,3], k = 2
Output: 7
Explanation: You can choose your jumps forming the subsequence [1,-1,4,3] (underlined above). The sum is 7.
I wrote a recursive solution in which we explore all the possibilies . If the function is called at index ind , then the value at index ind is added to a variable curSum for the next function call.
The base condition is when we reach the last index , we will return curSum+value of last index.
Here is the code:
class Solution {
static int min= Integer.MIN_VALUE;
public int maxResult(int[] nums, int k) {
return max(nums,0,k,0);
}
public int max(int [] nums, int ind, int k, int curSum)
{
if(ind==nums.length-1)
return curSum+nums[ind];
int max=Integer.MIN_VALUE;
for(int i=ind+1;i<=Math.min(nums.length-1,ind+k);i++)
max=Math.max(max, max(nums,i,k,curSum+nums[ind]));
return max;
}
}
Code works fine except the exponential complexity ofcourse.
I tried memoizing it as
class Solution {
static int[] dp;
static int min= Integer.MIN_VALUE;
public int maxResult(int[] nums, int k) {
dp=new int[nums.length];
Arrays.fill(dp,min);
return max(nums,0,k,0);
}
public int max(int [] nums, int ind, int k, int curSum)
{
if(ind==nums.length-1)
return curSum+nums[ind];
if(dp[ind]!=min)
return dp[ind];
int max=Integer.MIN_VALUE;
for(int i=ind+1;i<=Math.min(nums.length-1,ind+k);i++)
max=Math.max(max, max(nums,i,k,curSum+nums[ind]));
return dp[ind]=max;
}
}
But this solution gives the wrong max everytime and I am not quite able to figure out why.
Any hints will be appreciated.
Thanks
You only need to memoize dp[index] instead of calling f(index, currSum).
Take for example present arr.length = 5, k = 2
For index-2 you need wether index 3 or 4 gives better points to you irrespective of your present point.
Better way would be :
class Solution {
static int[] dp;
static int min= Integer.MIN_VALUE;
public int maxResult(int[] nums, int k) {
dp=new int[nums.length];
Arrays.fill(dp,min);
return max(nums,0,k,0);
}
public int max(int [] nums, int ind, int k, int curSum)
{
// base-case
if(ind==nums.length-1)
return curSum+nums[ind];
// if already memoized
if(dp[ind]!=min)
return dp[ind] + curSum;
// if not memoized, calculate value now
int max=Integer.MIN_VALUE;
for(int i=ind+1;i<=Math.min(nums.length-1,ind+k);i++)
max=Math.max(max, max(nums,i,k,nums[ind]);
// memoize here
dp[ind] = max
return dp[ind] + curSum;
}
}
The problem statement is :
Given an integer array A of size N.
You can pick B elements from either left or right end of the array A to get maximum sum.
Find and return this maximum possible sum.
NOTE: Suppose B = 4 and array A contains 10 elements then:
You can pick first four elements or can pick last four elements or can pick 1 from front and 3 from back etc . you need to return the maximum possible sum of elements you can pick.
public class Solution {
ArrayList<Integer> c = new ArrayList<>();
ArrayList<Integer> A= new ArrayList<>();
public int solve(ArrayList<Integer> A, int B) {
if (B>A.size()){
int sum=0;
for(int i=0;i<A.size();i++)
sum= sum+A.get(i);
return sum;
}
int max_sum=0;
for(int i=0;i<A.size();i++){
if((max_sum<suffix(A.size()-(B-i))+prefix(i-1)) ){
max_sum=suffix(A.size()-(B-i))+prefix(i-1);
}
}
return max_sum;
}
int prefix_sum=0;
int prefix(int a) {
for(int p=0;p<a+1;p++){
c=A;
prefix_sum=prefix_sum + c.get(p);
}
return prefix_sum;
}
int suffix_sum=0;
int suffix(int b){
c=A;
for(int q=b;q<c.size();q++){
suffix_sum=suffix_sum+c.get(q);
}
return suffix_sum;
}
}
I am getting runtime error, I have tried to implement the suffix and prefix methods which return the sum from the index[ 0, i] and sum from [i, N-i] respectively, then in the solve function I am trying to find the sum of prefix [a-1] +suffix[N-(b-a)] and find out the maximum sum, the syntax is completely correct, there is something wrong with the logic I assume, please help me find the correct solution by correcting this code instead of providing an alternative method
package com.array;
import java.util.Arrays;
import java.util.List;
public class PickFromBothSides {
public static void main(String[] args) {
Integer[] arr = { 5, -2, 3, 1, 2 };
System.out.println(solve(Arrays.asList(arr), 3));
}
public static int solve(List<Integer> A, int B) {
int n = A.size();
int result = 0;
for (int i = 0; i < B; i++) {
result += A.get(i);
}
int sum = result;
for (int i = 0; i < B; i++) {
sum -= A.get(B - 1 - i);
sum += A.get(n - 1 - i);
result = Math.max(result, sum);
}
return result;
}
}
Runtime O(n)
Space complexity O(1)
You are declaring int prefix_sum=0; and int suffix_sum=0; as fields, not as local variables of the respective methods.
You are calling suffix(A.size()-(B-i)) so with your example that is 10 - (4 -i) which is 6 + i. You iterate through i being in the range {0, ..., 10} so the value 6 + i will be all the numbers 6 through 16. You cannot index in the array above 9, so you get an exception.
You need to change
for(int i=0;i<A.size();i++){
to
for(int i=0; i <= B; i++){
because you are trying to ask each iteration "how many numbers are taken from the beginning"? 0, 1, 2, 3 or 4 if B is 4
Other upgrades:
You are calling suffix(A.size()-(B-i))+prefix(i-1)) twice in a row. Call it only once, store it in a variable and reuse.
You are calling prefix(i-1) but inside prefix() you are using the parameter a as a + 1. You don't need to subtract one and add one to the same thing
I am a beginner(first year uni student) programmer trying to solve this problem which i'm finding somewhat difficult. If you are to answer this question, don't provide me with a complex daunting algorithm that will leave me scratching my head. I'll really appreciate it if you explain it step my step (both logically/conceptually then through code)
The problem is as follows:image
I have tried to attempt it and my code only works for a certain case that i tested.
package com.company;
import java.lang.Math;
public class Main {
public static int[][] binary_partition(int array[], int k){
int x = (int) Math.pow(2,k);
int[][] partition = new int[((array.length/x)*2)][array.length/x];
int divisor = array.length/x;
if ((array.length % 2) != 0){
return partition;
}
if (divisor >= array.length-1){
return partition;
}
if (k==1){
return partition;
}
int p = 0;
for(int i=0;i<((array.length/x)*2);i++)
{
for (int j = 0; j<array.length/x;j++)
{
partition[i][j] = array[p];
p += 1;
}
}
return partition;
}
public static void main(String[] args){
int[] array = {3, 2, 4, 7, 8, 9, 2, 3};
int[][] result = binary_partition(array,2);
for (int[] x : result){
for (int y : x)
{
System.out.print(y + " ");
}
System.out.println();
}
}
}
Your question is unclear, but this solution creates a function that partitions an array with the right length into 2^k sets.
First, an interesting fact: using the bitshift operator << on an integer increases its value by a power of two. So to find out the size of your partition, you could write
int numPartitions = 1 << k; // Equivalent to getting the integer value of 2^k
With this fact, the function becomes
public static int[][] partition(int[] set, int k) {
if (set == null)
return null; // Don't try to partition a null reference
// If k = 0, the partition of the set is just the set
if (k == 0) {
int[][] partition = new int[1][set.length];
// Copy the original set into the partition
System.arraycopy(set, 0, partition[0], 0, set.length);
return partition;
}
int numPartitions = 1 << k; // The number of sets to partition the array into
int numElements = set.length / numPartitions; // The number of elements per partition
/* Check if the set has enough elements to create a partition and make sure
that the partitions are even */
if (numElements == 0 || set.length % numElements != 0)
return null; // Replace with an error/exception of your choice
int[][] partition = new int[numPartitions][numElements];
int index = 0;
for (int r = 0; r < numPartitions; r++) {
for (int c = 0; c < numElements; c++) {
partition[r][c] = set[index++]; // Assign an element to the partition
}
}
return partition;
}
There are a few lines of your code where the intention is not clear. For example, it is not clear why you are validating divisor >= array.length-1. Checking k==1 is also incorrect because k=1 is a valid input to the method. In fact, all your validation checks are not needed. All you need to validate is that array.length is divisible by x.
The main problem that you have seems to be that you mixed up the lengths of the resulting array.
The resulting array should have a length of array.length / x, and each of the subarrays should have a length of x, hence:
int[][] partition = new int[array.length/x][x];
If you also fix your bounds on the for loops, your code should work.
Your nested for loop can be rewritten as a single for loop:
for(int i = 0 ; i < array.length ; i++)
{
int index = i / x;
int subArrayIndex = i % x;
partition[index][subArrayIndex] = array[i];
}
You just need to figure out which indices a an element array[i] belongs by dividing and getting the remainder.
I'm solving Codility questions as practice and couldn't answer one of the questions. I found the answer on the Internet but I don't get how this algorithm works. Could someone walk me through it step-by-step?
Here is the question:
/*
You are given integers K, M and a non-empty zero-indexed array A consisting of N integers.
Every element of the array is not greater than M.
You should divide this array into K blocks of consecutive elements.
The size of the block is any integer between 0 and N. Every element of the array should belong to some block.
The sum of the block from X to Y equals A[X] + A[X + 1] + ... + A[Y]. The sum of empty block equals 0.
The large sum is the maximal sum of any block.
For example, you are given integers K = 3, M = 5 and array A such that:
A[0] = 2
A[1] = 1
A[2] = 5
A[3] = 1
A[4] = 2
A[5] = 2
A[6] = 2
The array can be divided, for example, into the following blocks:
[2, 1, 5, 1, 2, 2, 2], [], [] with a large sum of 15;
[2], [1, 5, 1, 2], [2, 2] with a large sum of 9;
[2, 1, 5], [], [1, 2, 2, 2] with a large sum of 8;
[2, 1], [5, 1], [2, 2, 2] with a large sum of 6.
The goal is to minimize the large sum. In the above example, 6 is the minimal large sum.
Write a function:
class Solution { public int solution(int K, int M, int[] A); }
that, given integers K, M and a non-empty zero-indexed array A consisting of N integers, returns the minimal large sum.
For example, given K = 3, M = 5 and array A such that:
A[0] = 2
A[1] = 1
A[2] = 5
A[3] = 1
A[4] = 2
A[5] = 2
A[6] = 2
the function should return 6, as explained above. Assume that:
N and K are integers within the range [1..100,000];
M is an integer within the range [0..10,000];
each element of array A is an integer within the range [0..M].
Complexity:
expected worst-case time complexity is O(N*log(N+M));
expected worst-case space complexity is O(1), beyond input storage (not counting the storage required for input arguments).
Elements of input arrays can be modified.
*/
And here is the solution I found with my comments about parts which I don't understand:
public static int solution(int K, int M, int[] A) {
int lower = max(A); // why lower is max?
int upper = sum(A); // why upper is sum?
while (true) {
int mid = (lower + upper) / 2;
int blocks = calculateBlockCount(A, mid); // don't I have specified number of blocks? What blocks do? Don't get that.
if (blocks < K) {
upper = mid - 1;
} else if (blocks > K) {
lower = mid + 1;
} else {
return upper;
}
}
}
private static int calculateBlockCount(int[] array, int maxSum) {
int count = 0;
int sum = array[0];
for (int i = 1; i < array.length; i++) {
if (sum + array[i] > maxSum) {
count++;
sum = array[i];
} else {
sum += array[i];
}
}
return count;
}
// returns sum of all elements in an array
private static int sum(int[] input) {
int sum = 0;
for (int n : input) {
sum += n;
}
return sum;
}
// returns max value in an array
private static int max(int[] input) {
int max = -1;
for (int n : input) {
if (n > max) {
max = n;
}
}
return max;
}
So what the code does is using a form of binary search (How binary search works is explained quite nicely here, https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/. It also uses an example quite similar to your problem.). Where you search for the minimum sum every block needs to contain. In the example case, you need the divide the array in 3 parts
When doing a binary search you need to define 2 boundaries, where you are certain that your answer can be found in between. Here, the lower boundary is the maximum value in the array (lower). For the example, this is 5 (this is if you divide your array in 7 blocks). The upper boundary (upper) is 15, which is the sum of all the elements in the array (this is if you divide the array in 1 block.)
Now comes the search part: In solution() you start with your bounds and mid point (10 for the example).
In calculateBlockCount you count (count ++ does that) how many blocks you can make if your sum is a maximum of 10 (your middle point/ or maxSum in calculateBlockCount).
For the example 10 (in the while loop) this is 2 blocks, now the code returns this (blocks) to solution. Then it checks whether is less or more than K, which is the number of blocks you want. If its less than K your mid point is high because you're putting to many array elements in your blocks. If it's more than K, than your mid point is too high and you're putting too little array elements in your array.
Now after the checking this, it halves the solution space (upper = mid-1).
This happens every loop, it halves the solution space which makes it converge quite quickly.
Now you keep going through your while adjusting the mid, till this gives the amount blocks which was in your input K.
So to go though it step by step:
Mid =10 , calculateBlockCount returns 2 blocks
solution. 2 blocks < K so upper -> mid-1 =9, mid -> 7 (lower is 5)
Mid =7 , calculateBlockCount returns 2 blocks
solution() 2 blocks < K so upper -> mid-1 =6, mid -> 5 (lower is 5, cast to int makes it 5)
Mid =5 , calculateBlockCount returns 4 blocks
solution() 4 blocks < K so lower -> mid+1 =6, mid -> 6 (lower is 6, upper is 6
Mid =6 , calculateBlockCount returns 3 blocks
So the function returns mid =6....
Hope this helps,
Gl learning to code :)
Edit. When using binary search a prerequisite is that the solution space is a monotonic function. This is true in this case as when K increases the sum is strictly decreasing.
Seems like your solution has some problems. I rewrote it as below:
class Solution {
public int solution(int K, int M, int[] A) {
// write your code in Java SE 8
int high = sum(A);
int low = max(A);
int mid = 0;
int smallestSum = 0;
while (high >= low) {
mid = (high + low) / 2;
int numberOfBlock = blockCount(mid, A);
if (numberOfBlock > K) {
low = mid + 1;
} else if (numberOfBlock <= K) {
smallestSum = mid;
high = mid - 1;
}
}
return smallestSum;
}
public int sum(int[] A) {
int total = 0;
for (int i = 0; i < A.length; i++) {
total += A[i];
}
return total;
}
public int max(int[] A) {
int max = 0;
for (int i = 0; i < A.length; i++) {
if (max < A[i]) max = A[i];
}
return max;
}
public int blockCount(int max, int[] A) {
int current = 0;
int count = 1;
for (int i = 0; i< A.length; i++) {
if (current + A[i] > max) {
current = A[i];
count++;
} else {
current += A[i];
}
}
return count;
}
}
This is helped me in case anyone else finds it helpful.
Think of it as a function: given k (the block count) we get some largeSum.
What is the inverse of this function? It's that given largeSum we get a k. This inverse function is implemented below.
In solution() we keep plugging guesses for largeSum into the inverse function until it returns the k given in the exercise.
To speed up the guessing process, we use binary search.
public class Problem {
int SLICE_MAX = 100 * 1000 + 1;
public int solution(int blockCount, int maxElement, int[] array) {
// maxGuess is determined by looking at what the max possible largeSum could be
// this happens if all elements are m and the blockCount is 1
// Math.max is necessary, because blockCount can exceed array.length,
// but this shouldn't lower maxGuess
int maxGuess = (Math.max(array.length / blockCount, array.length)) * maxElement;
int minGuess = 0;
return helper(blockCount, array, minGuess, maxGuess);
}
private int helper(int targetBlockCount, int[] array, int minGuess, int maxGuess) {
int guess = minGuess + (maxGuess - minGuess) / 2;
int resultBlockCount = inverseFunction(array, guess);
// if resultBlockCount == targetBlockCount this is not necessarily the solution
// as there might be a lower largeSum, which also satisfies resultBlockCount == targetBlockCount
if (resultBlockCount <= targetBlockCount) {
if (minGuess == guess) return guess;
// even if resultBlockCount == targetBlockCount
// we keep searching for potential lower largeSum that also satisfies resultBlockCount == targetBlockCount
// note that the search range below includes 'guess', as this might in fact be the lowest possible solution
// but we need to check in case there's a lower one
return helper(targetBlockCount, array, minGuess, guess);
} else {
return helper(targetBlockCount, array, guess + 1, maxGuess);
}
}
// think of it as a function: given k (blockCount) we get some largeSum
// the inverse of the above function is that given largeSum we get a k
// in solution() we will keep guessing largeSum using binary search until
// we hit k given in the exercise
int inverseFunction(int[] array, int largeSumGuess) {
int runningSum = 0;
int blockCount = 1;
for (int i = 0; i < array.length; i++) {
int current = array[i];
if (current > largeSumGuess) return SLICE_MAX;
if (runningSum + current <= largeSumGuess) {
runningSum += current;
} else {
runningSum = current;
blockCount++;
}
}
return blockCount;
}
}
From anhtuannd's code, I refactored using Java 8. It is slightly slower. Thanks anhtuannd.
IntSummaryStatistics summary = Arrays.stream(A).summaryStatistics();
long high = summary.getSum();
long low = summary.getMax();
long result = 0;
while (high >= low) {
long mid = (high + low) / 2;
AtomicLong blocks = new AtomicLong(1);
Arrays.stream(A).reduce(0, (acc, val) -> {
if (acc + val > mid) {
blocks.incrementAndGet();
return val;
} else {
return acc + val;
}
});
if (blocks.get() > K) {
low = mid + 1;
} else if (blocks.get() <= K) {
result = mid;
high = mid - 1;
}
}
return (int) result;
I wrote a 100% solution in python here. The result is here.
Remember: You are searching the set of possible answers not the array A
In the example given they are searching for possible answers. Consider [5] as 5 being the smallest max value for a block. And consider [2, 1, 5, 1, 2, 2, 2] 15 as the largest max value for a block.
Mid = (5 + 15) // 2. Slicing out blocks of 10 at a time won't create more than 3 blocks in total.
Make 10-1 the upper and try again (5+9)//2 is 7. Slicing out blocks of 7 at a time won't create more than 3 blocks in total.
Make 7-1 the upper and try again (5+6)//2 is 5. Slicing out blocks of 5 at a time will create more than 3 blocks in total.
Make 5+1 the lower and try again (6+6)//2 is 6. Slicing out blocks of 6 at a time won't create more than 3 blocks in total.
Therefore 6 is the lowest limit to impose on the sum of a block that will permit breaking into 3 blocks.
Given an array of integers, which can contain both +ve and -ve numbers. I've to maximize the product of any 3 elements of the array. The elements can be non-contiguous.
Some examples:
int[] arr = {-5, -7, 4, 2, 1, 9}; // Max Product of 3 numbers = -5 * -7 * 9
int[] arr2 = {4, 5, -19, 3}; // Max Product of 3 numbers = 4 * 5 * 3
I've tried solving it using Dynamic Programming, but I'm not getting the expected result. It is returning the result often involving the same number twice in the multiplication. So, for the array - {4, 2, 1, 9}, it is returning - 32, which is 4 * 4 * 2.
Here's my code:
public static int maxProduct(int[] arr, int count) {
return maxProduct(arr, 0, arr.length - 1, count);
}
private static int maxProduct(int[] arr, int fromIndex, int toIndex, int count) {
if (count == 1) {
return maximum(arr, fromIndex, toIndex);
} else if (toIndex - fromIndex + 1 < count) {
return 1;
} else {
return MathUtil.max(maxProduct(arr, fromIndex, toIndex - 1, count - 1) * arr[toIndex - 1],
maxProduct(arr, fromIndex, toIndex - 1, count));
}
}
MathUtil.max(int a, int b) is a method that gives maximum of a and b.
The two values I pass to max method there are:
maxProduct, when we consider last element as a part of product.
maxProduct, when we don't consider it as a part of product.
count contains the number of element we want to consider. Here 3.
For count == 1, we have to find maximum of 1 element from array. That means, we have to use maximum array element.
If toIndex - fromIndex + 1 < count, means, there are not enough elements in the array between those indices.
I've an intuition that, the first if condition is one of the reason of failure. Because, it is only considering maximum element from an array, while the maximum product may comprise of negative numbers too. But I don't know how to take care of that.
The reason I'm using Dynamic Programming is that I can then generalize this solution to work for any value of count. Of course, if someone have any better approach, even for count = 3, I welcome the suggestion (I would want to avoid sorting the array, as that will be another O(nlogn) at the least).
Sort the given array in ascending order and you have to take the maximum of these cases
to get the answer..
product of last 3 numbers in sorted array
Product of first two and last number in the sorted array
For count=3, your solution will have 1 of 3 forms:
The 3 largest positive values (assuming there ARE 3 positive values)
The largest positive value and the 2 smallest negative values (assuming there IS a positive value)
The 3 least negative values
Each of which can be solved a lot easier than using DP.
It is always max of(smallest two negative digits and biggest positive or
last three big positive numbers)
public static void main(String args[]){
int array[] = {-5,-1,4,2,1,9};
Arrays.sort(array);
int length = array.length;
System.out.println(max(array[0]*array[1]*array[length-1],
array[length-1]*array[length-2]*array[length-3]));
}
Sort The Array
Then max will be either the product of last 3 or first 2(if negative) and the last.
Arrays.sort(arr);
int max1 = (arr[n - 1] * arr[n - 2] * arr[n - 3]);
int max2 = (arr[0] * arr[1] * arr[n - 1]);
System.out.println(max1 > max2 ? max1 : max2);
n=len(arr1)
for i in range(0,n):
arr1[i]=abs(arr1[i])
arr1.sort()
return arr1[n-1]*arr1[n-2]*arr1[n-3]
even though this solution is simple this basically involves sorting the array and then taking the product of last three numbers , before that is to be done ; all the values in the array should be positive .which is done by the first for loop.
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
public class ComputeMaxProduct {
public static void main(String[] args){
int [] arr = {4, 5, -19, 3};
List<Integer> superSet = new ArrayList<>();
for (int a : arr ){
superSet.add(a);
}
int k = 3;
int maxProduct = computeMaxProduct(superSet, k);
System.out.println("maximum product is : " + maxProduct);
}
private static int computeMaxProduct( List<Integer> superSet, int k ){
List<Set<Integer>> res = getSubsets(superSet,k);
int maxProduct = 1;
for(int index = 0; index < res.size(); index++){
int product = 1;
for(Integer i : res.get(index)){
product *= i;
}
if (product > maxProduct){
maxProduct = product;
}
}
return maxProduct;
}
private static void getSubsets(List<Integer> superSet, int k, int idx, Set<Integer> current,List<Set<Integer>> solution) {
//successful stop clause
if (current.size() == k) {
solution.add(new HashSet<>(current));
return;
}
//unseccessful stop clause
if (idx == superSet.size()) return;
Integer x = superSet.get(idx);
current.add(x);
//"guess" x is in the subset
getSubsets(superSet, k, idx+1, current, solution);
current.remove(x);
//"guess" x is not in the subset
getSubsets(superSet, k, idx+1, current, solution);
}
public static List<Set<Integer>> getSubsets(List<Integer> superSet, int k) {
List<Set<Integer>> res = new ArrayList<>();
getSubsets(superSet, k, 0, new HashSet<Integer>(), res);
return res;
}
}
public class MaxProdofThreenumbers {
public int ThreeLargeNumbers(int[] a) {
int topfirstpos = 0;
int topsecpos = 0;
int topthirdpos = 0;
int topfirstneg = 0;
int topsecneg = 0;
int prodneg = 0;
int prodpos = 0;
int prodmax = 0;
boolean flag = false;
for (int i = 0; i < a.length; i++) {
String num = a[i] + "";
if (num.contains("-")) {
String array[] = num.split("-");
num = array[1];
flag = true;
} else
flag = false;
if (flag) {
if (topfirstneg < Integer.valueOf(num)) {
topsecneg = topfirstneg;
topfirstneg = Integer.valueOf(num);
} else if (topsecneg < Integer.valueOf(num)) {
topsecneg = Integer.valueOf(num);
}
}
else {
if (topfirstpos < Integer.valueOf(num)) {
topsecpos = topfirstpos;
topfirstpos = Integer.valueOf(num);
}
else if (topsecpos < Integer.valueOf(num)) {
topthirdpos = topsecpos;
topsecpos = Integer.valueOf(num);
}
else if (topthirdpos < Integer.valueOf(num)) {
topthirdpos = Integer.valueOf(num);
}
}
}
prodneg = topfirstneg * topsecneg;
prodpos = topfirstpos * topsecpos;
if (prodneg > prodpos) {
prodmax = prodneg * topfirstpos;
} else {
prodmax = prodpos * topthirdpos;
}
return prodmax;
}
public static void main(String a[]) {
int list[] = { -29, 3, -2, -57, 8, -789, 34 };
MaxProdofThreenumbers t = new MaxProdofThreenumbers();
System.out.println(t.ThreeLargeNumbers(list));
}
}
This problem can be done in O(n) time.
Keep track of these 5 variables and update them during every iteration:
highest product of 3 numbers
highest product of 2 numbers
highest element
lowest product of 2 numbers
lowest element
After last iteration, product of 3 numbers variable will be the answer.
package interviewProblems;
import interviewProblems.exceptions.ArrayTooSmallException;
import java.util.PriorityQueue;
public class Problem5 {
public static void main(String[] args) {
int[] data1 = new int[]{}; // error
int[] data2 = new int[]{1, 5}; // error
int[] data3 = new int[]{1, 4, 2, 8, 9}; // Case: all positive --> 3-max
int[] data4 = new int[]{10, 11, 12, -20}; // Case: 1 negative --> 3-max
int[] data5 = new int[]{-5, -6, -10, 7, 8, 9}; // Case: 2+ negative --> 3-max || 1-max 2-small
int[] data6 = new int[]{-12, -10, -6, -4}; // Case: all negative --> 3-max
int[] data7 = new int[]{-10, -10, 1, 3, 2};
try {
productOfThree(data2);
} catch (Exception e) {
System.out.println(e.getMessage());
}
try {
System.out.println(productOfThree(data3));
System.out.println(productOfThree(data4));
System.out.println(productOfThree(data5));
System.out.println(productOfThree(data6));
System.out.println(productOfThree(data7));
} catch (Exception e) {
System.out.println("You should not see this line");
}
}
// O(n) time
// O(1) memory
private static int productOfThree(int[] data) throws ArrayTooSmallException {
if (data.length < 3) {
throw new ArrayTooSmallException(3 , data.length);
}
PriorityQueue<Integer> maxNumbers = new PriorityQueue<>(); // keep track of 3 largest numbers
PriorityQueue<Integer> minNumbers = new PriorityQueue<>((x, y) -> y - x); // keep track of two smallest numbers
for (int i = 0; i < data.length; i++) {
maxNumbers.add(data[i]);
minNumbers.add(data[i]);
if(maxNumbers.size() > 3) {
maxNumbers.poll();
}
if(minNumbers.size() > 2){
minNumbers.poll();
}
}
int maxLow = maxNumbers.poll();
int maxMed = maxNumbers.poll();
int maxHigh = maxNumbers.poll();
int minHigh = minNumbers.poll();
int minLow = minNumbers.poll();
int possibleProduct1 = maxHigh * maxMed * maxLow;
int possibleProduct2 = maxHigh * minHigh * minLow;
return Math.max(possibleProduct1, possibleProduct2);
}
// O(n) time
// O(n) memory
// private static int productOfThree(int[] data) throws ArrayTooSmallException {
// if(data.length < 3) {
// throw new ArrayTooSmallException("Array must be at least 3 long to preform productOfThree(int[] data)");
// }
//
// PriorityQueue<Integer> maxNumbers = new PriorityQueue<>((x , y) -> y - x); // keep track of 3 largest numbers
// PriorityQueue<Integer> minNumbers = new PriorityQueue<>(); // keep track of two smallest numbers
//
// for(int i = 0; i < data.length; i++) {
// maxNumbers.add(data[i]);
// minNumbers.add(data[i]);
// }
//
// int maxHigh = maxNumbers.poll();
// int maxMed = maxNumbers.poll();
// int maxLow = maxNumbers.poll();
//
// int minLow = minNumbers.poll();
// int minHigh = minNumbers.poll();
//
// int possibleProduct1 = maxHigh * maxMed * maxLow;
// int possibleProduct2 = maxHigh * minHigh * minLow;
//
// return Math.max(possibleProduct1 , possibleProduct2);
// }
}
https://github.com/amilner42/interviewPractice/blob/master/src/interviewProblems/Problem5.java
Assuming that the a positive product is bigger than a negative product, I can think of the following way it can be done.
If there are less than two negative elements in the array, then it is simple, product of top 3(top == positive) elements.
If negative numbers are chosen, at least 2 of them have to be in the product, so that product is positive. Therefore whatever be the case, the top (positive) number will always be part of the product.
Multiply last two(negatives) and 2nd and 3rd highest(positives) and compare. Out of these two pairs whichever has higher value, will be part of the final product along with the top positive shortlisted in line above.
https://stackoverflow.com/users/2466168/maandoo 's answer is the best.
As, he said, answer is max(l,r) for
r. product of last 3 numbers in sorted array
l. product of first two and last number in the sorted array
Let me elaborate now.
I think this problem is confusion because each number can be positive, negative and zero. 3 state is annoying to mange by programming, you know!
Case 1) Given three numbers
Use them all
Case 2) Given four numbers
Positive number is show +, Negative number is show -.
Numbers are sorted from left to right.
Case 2-1)
2-1) ---- => r (answer is negative)
2-2) ---+ => l (answer is positive)
2-3) --++ => l (answer is positive)
2-4) -+++ => r (answer is positive)
2-5) ++++ => r (answer is positive)
When a 0 is mixed in four numbers, it comes between
- and +.
Case 2-2)
Suppose smallest + was actually 0.
2-1) ---- => r (answer is negative)
2-2) ---0 => l (answer is 0)
2-3) --0+ => l (answer is positive)
2-4) -0++ => r (answer is 0)
2-5) 0+++ => r (answer is positive)
Case 2-3)
Suppose largest - was actually 0.
2-1) ---0 => r (answer is 0)
2-2) --0+ => l (answer is positive)
2-3) -0++ => l (answer is 0)
2-4) 0+++ => r (answer is positive)
2-5) ++++ => r (answer is positive)
Case 2-4)
If more than two 0 is mixed, products becomes always 0 because
-00+
Summary for Case 2)
answer is consistent among Case 2-1 ~ 2-4.
2-1) r (negative or 0)
2-2) l (0 or positive)
2-3) l (0 or positive)
2-4) r (0 or positive)
2-5) r (positive)
So, we do not need to worry about 0 actually.
Case 3) More than four numbers
The same with Case 2
u have to consider 3 cases:
1. max 3 positive elements can be the first answer(say 10*20*70).
2. max positive elements multiplied by 2 most negative answers is another candidate(say20*-40*-60).
3.in case where all array elements are negative,3 elements with minimum negative magnitude is answer(-1*-2*-3 in [-1,-2,3,-4,-5]).
for simplicity of question we can merge 1st and 3rd case.
find 3 maximum elements of array, similarly find 2 minimum elements of array.
u will get 2 candidates. Print the maximum of those candidates.
C++ Code:
#include <iostream>
#include <limits.h>
using namespace std;
int main()
{
int n; cin>>n; int arr[n]; for(int a=0;a<n;a++) cin>>arr[a];
bool flag=0;
int max1=INT_MIN,max2=INT_MIN,max3=INT_MIN;
int min1=INT_MAX,min2=INT_MAX;
for(int a=0;a<n;a++)
{
if(arr[a]>max1) {max3=max2; max2=max1; max1=arr[a];}
else if(arr[a]>max2) {max3=max2; max2=arr[a];}
else if(arr[a]>max3) max3=arr[a]; flag=1;
if(arr[a]<min1) {min2=min1; min1=arr[a];}
else if(arr[a]<min2) min2=arr[a];
}
int prod1=INT_MIN,prod2=INT_MIN;
if(max1>INT_MIN && max2>INT_MIN && max3>INT_MIN) prod1=max1*max2*max3;
if(max1>INT_MIN && min1<INT_MAX && min2<INT_MAX) prod2=max1*min1*min2;
cout<<max(prod1,prod2)<<endl;
}
// Here is a simple java program to find the maximum product of three numbers in an array.
import java.util.*;
import java.lang.*;
class MOHAN_BERA
{
public static void main(String[] args)
{
Scanner s = new Scanner(System.in);
System.out.println("enter the lenth of array:");
int num1=s.nextInt();
int[] num2=new int[num1];
System.out.println("enter the numbers of array:");
for(int i=0;i<num1;i++)
{
num2[i]=s.nextInt();
}
Arrays.sort(num2);//sort the array
long max1=num2[num1-1]*num2[num1-2]*num2[num1-3];//Three last numbers, can be three positive numbers
long max2=num2[num1-1]*num2[0]*num2[1];//last numbers and first two numbers,can be first two negetive and last one positive numbers
long max3=num2[0]*num2[1]*num2[2];//for all negetives numbers
long max=max1;//max1 greatest
if(max<max2 && max3<max2) //max2 greatest
{
max=max2;
}
else if(max<max3 && max2<max3)//max3 greatest
{
max=max3;
}
System.out.println(max);
}
}
in JavaScript
function largestProduct(ints) {
ints.sort((a, b) => b - a);
return ints[0] * ints[1] * ints[2];
}
Language - C#
Greedy Approach
Time Complexity O(n)
public static int GetHighestProductOfThree(int[] arrayOfInts)
{
if (arrayOfInts.Length < 3)
{
throw new ArgumentException("Array should be atleast 3 items", nameof(arrayOfInts));
}
int highest = Math.Max(arrayOfInts[0], arrayOfInts[1]);
int lowest = Math.Min(arrayOfInts[0], arrayOfInts[1]);
int highestProductOf2 = arrayOfInts[0] * arrayOfInts[1];
int lowestProductOf2 = arrayOfInts[0] * arrayOfInts[1];
int highestProductOf3 = arrayOfInts[0] * arrayOfInts[1] * arrayOfInts[2];
for (int i = 2; i < arrayOfInts.Length; i++)
{
int current = arrayOfInts[i];
highestProductOf3 = Math.Max(Math.Max(
highestProductOf3,
current * highestProductOf2),
current * lowestProductOf2);
highestProductOf2 = Math.Max(Math.Max(
highestProductOf2,
current * highest),
current * lowest);
lowestProductOf2 = Math.Min(Math.Min(
lowestProductOf2,
current * highest),
current * lowest);
highest = Math.Max(highest, current);
lowest = Math.Min(lowest, current);
}
return highestProductOf3;
}
Thanks to interviewcake.com
Detailed Explanation of this Algorithm
def solution(A):
if len(A) < 3:
return 0
A.sort()
product = A[len(A)-1] * A[len(A)-2] * A[len(A)-3]
if A[0] < 0 and A[1] < 0:
if A[0] * A[1] * A[len(A)-1] > product:
product = A[0] * A[1] * A[len(A)-1]
return product
Below is my solution in JavaScript:
function solution(A) {
A = A.sort((a, b) => b - a);
var product = A[0] * A[1] * A[2];
var length = A.length;
if (A[0] < 0) return product;
if (A[length - 1] * A[length - 2] * A[0] > product) {
return A[length - 1] * A[length - 2] * A[0];
}
if (A[2] < 0 && length >= 5 && A[3] * A[4] < A[0] * A[1]) {
return A[2] * A[3] * A[4];
}
return product;
}
This Solution is applicable only if there are 3 numbers needed. If It's dynamic or say user can ask for 4 or 5 then this solution is not suitable for it.
Without sorting you can achieve it by find out max 3 numbers from array and multiply 3 numbers, because max product requires max number from array.
public class FindOutProductPair {
public static void main(String args[]) {
int arr[]= {2,4,3,6,12,1};
// int arr1[]= {2,4,3,7,6,5,1};
// int arr1[]= {-1,-4,3,7,6,5,1};
int arr1[]= {3,2};
int max1=1,max2=1,max3=1;
for(int i=0;i<arr1.length;i++) {
if(max1 < arr1[i]) {
max3=max2;
max2=max1;
max1=arr1[i];
}else {
if(max2 < arr1[i]) {
max3=max2;
max2=arr1[i];
}
else {
if(max3< arr1[i]) {
max3=arr1[i];
}
}
}
}
System.out.println((max3+" "+max2+" "+max1)+" <-- "+(max3*max2*max1));
}
}
Could be like this in JAVA:
public final static int maxProizvedenieTrexChisel(Integer m []){
Arrays.sort(m,(g,g1)->g-g1);
System.out.println(Arrays.toString(m));
int mx1=m[0]*m[1]*m[2];
int mx2=m[m.length-1]*m[m.length-2]*m[m.length-3];
int mx3=m[0]*m[1]*m[m.length-1];
if(mx1>mx2&mx1>mx3)
return mx1;
else if(mx2>mx1&mx2>mx3)
return mx2;
return mx3;
}
could be solve using 5 variables with O(n) pass.
Max Product can be formed by either:
1. Max1 * Max2 * Max3
2. Max1 * Min1 * min2
where Max is maximum element and Min stands for minimum.
Here is my Java solution:
int maxProduct(int[] arr) {
int max1, max2, max3 = Integer.MIN_VALUE;
max1 = max3;
max2 = max3;
int min1 = Integer.MAX_VAULE;
int min2 = Integer.MAX_VAULE;
for(int n : arr) {
if (n <= min1) { // n is smaller than all
min2 = min1;
min1 = n;
} else if (n < min2) { // n lies between min1 and min2
min2 = n;
}
if (n >= max1) { // n is greater than all
max3 = max2;
max2 = max1;
max1 = n;
} else if (n >= max2) { // n lies betweeen max1 and max2
max3 = max2;
max2 = n;
} else if (n > max3) { // n lies betwen max2 and max3
max3 = n;
}
}
}
JavaScript code
function solution(A) {
if(A.length<3){
return 0;
}
let maxElement = Number.NEGATIVE_INFINITY;
let idx = null;
for(let i=0;i<A.length;i++){
if(A[i]>maxElement){
maxElement = A[i];
idx = i;
}
}
A.splice(idx,1);
A.sort((a,b)=>b-a);
let n = A.length;
let positiveMax = A[0]*A[1]*maxElement;
let negativeMax = A[n-1]*A[n-2]*maxElement;
return Math.max(positiveMax,negativeMax);
}
You can use inbuilt sort function of Javascript.Need to careful while finding max triplet product as in case of array with -ve numbers product will be combination first 2 and last and in case all +ve last 3 number product will be result.You can refer my jsfiddle. Also complexity of this algorithm is O(nlogn)
var arr=[-10, 3, 5, 6, -20];
function maxTripletProduct(data)
{
var sortedarr=data.sort(function(a,b){
return a-b;
})
console.log(sortedarr);
let length=sortedarr.length;
let product1 = sortedarr[length-3]*sortedarr[length-2]*sortedarr[length-1]
let product2=sortedarr[0]*sortedarr[1]*sortedarr[length-1];
if(product2>product1)
console.log(product2);
else
console.log(product1);
}
maxTripletProduct(arr);