I was asked this question in a job interview, and I'd like to know how others would solve it. I'm most comfortable with Java, but solutions in other languages are welcome.
Given an array of numbers,
nums, return an array of numbersproducts, whereproducts[i]is the product of allnums[j], j != i.Input : [1, 2, 3, 4, 5] Output: [(2*3*4*5), (1*3*4*5), (1*2*4*5), (1*2*3*5), (1*2*3*4)] = [120, 60, 40, 30, 24]You must do this in
O(N)without using division.
Well,this solution can be considered that of C/C++. Lets say we have an array "a" containing n elements like a[n],then the pseudo code would be as below.
for(j=0;j<n;j++)
{
prod[j]=1;
for (i=0;i<n;i++)
{
if(i==j)
continue;
else
prod[j]=prod[j]*a[i];
}
def productify(arr, prod, i):
if i < len(arr):
prod.append(arr[i - 1] * prod[i - 1]) if i > 0 else prod.append(1)
retval = productify(arr, prod, i + 1)
prod[i] *= retval
return retval * arr[i]
return 1
arr = [1, 2, 3, 4, 5] prod = [] productify(arr, prod, 0) print prod
A variation in JavaScript using reduce
const getProduct = arr => arr.reduce((acc, value) => acc * value);_x000D_
_x000D_
const arrayWithExclusion = (arr, node) =>_x000D_
arr.reduce((acc, val, j) => (node !== j ? [...acc, val] : acc), []);_x000D_
_x000D_
const getProductWithExclusion = arr => {_x000D_
let result = [];_x000D_
_x000D_
for (let i = 0; i < arr.length; i += 1) {_x000D_
result.push(getProduct(arrayWithExclusion(arr, i)));_x000D_
}_x000D_
_x000D_
return result;_x000D_
};int[] b = new int[] { 1, 2, 3, 4, 5 };
int j;
for(int i=0;i<b.Length;i++)
{
int prod = 1;
int s = b[i];
for(j=i;j<b.Length-1;j++)
{
prod = prod * b[j + 1];
}
int pos = i;
while(pos!=-1)
{
pos--;
if(pos!=-1)
prod = prod * b[pos];
}
Console.WriteLine("\n Output is {0}",prod);
}
Here is simple Scala version in Linear O(n) time:
def getProductEff(in:Seq[Int]):Seq[Int] = {
//create a list which has product of every element to the left of this element
val fromLeft = in.foldLeft((1, Seq.empty[Int]))((ac, i) => (i * ac._1, ac._2 :+ ac._1))._2
//create a list which has product of every element to the right of this element, which is the same as the previous step but in reverse
val fromRight = in.reverse.foldLeft((1,Seq.empty[Int]))((ac,i) => (i * ac._1,ac._2 :+ ac._1))._2.reverse
//merge the two list by product at index
in.indices.map(i => fromLeft(i) * fromRight(i))
}
This works because essentially the answer is an array which has product of all elements to the left and to the right.
Here's my attempt to solve it in Java. Apologies for the non-standard formatting, but the code has a lot of duplication, and this is the best I can do to make it readable.
import java.util.Arrays;
public class Products {
static int[] products(int... nums) {
final int N = nums.length;
int[] prods = new int[N];
Arrays.fill(prods, 1);
for (int
i = 0, pi = 1 , j = N-1, pj = 1 ;
(i < N) && (j >= 0) ;
pi *= nums[i++] , pj *= nums[j--] )
{
prods[i] *= pi ; prods[j] *= pj ;
}
return prods;
}
public static void main(String[] args) {
System.out.println(
Arrays.toString(products(1, 2, 3, 4, 5))
); // prints "[120, 60, 40, 30, 24]"
}
}
The loop invariants are pi = nums[0] * nums[1] *.. nums[i-1] and pj = nums[N-1] * nums[N-2] *.. nums[j+1]. The i part on the left is the "prefix" logic, and the j part on the right is the "suffix" logic.
Jasmeet gave a (beautiful!) recursive solution; I've turned it into this (hideous!) Java one-liner. It does in-place modification, with O(N) temporary space in the stack.
static int multiply(int[] nums, int p, int n) {
return (n == nums.length) ? 1
: nums[n] * (p = multiply(nums, nums[n] * (nums[n] = p), n + 1))
+ 0*(nums[n] *= p);
}
int[] arr = {1,2,3,4,5};
multiply(arr, 1, 0);
System.out.println(Arrays.toString(arr));
// prints "[120, 60, 40, 30, 24]"
Here is my code:
int multiply(int a[],int n,int nextproduct,int i)
{
int prevproduct=1;
if(i>=n)
return prevproduct;
prevproduct=multiply(a,n,nextproduct*a[i],i+1);
printf(" i=%d > %d\n",i,prevproduct*nextproduct);
return prevproduct*a[i];
}
int main()
{
int a[]={2,4,1,3,5};
multiply(a,5,1,0);
return 0;
}
import java.util.Arrays;
public class Pratik
{
public static void main(String[] args)
{
int[] array = {2, 3, 4, 5, 6}; // OUTPUT: 360 240 180 144 120
int[] products = new int[array.length];
arrayProduct(array, products);
System.out.println(Arrays.toString(products));
}
public static void arrayProduct(int array[], int products[])
{
double sum = 0, EPSILON = 1e-9;
for(int i = 0; i < array.length; i++)
sum += Math.log(array[i]);
for(int i = 0; i < array.length; i++)
products[i] = (int) (EPSILON + Math.exp(sum - Math.log(array[i])));
}
}
OUTPUT:
[360, 240, 180, 144, 120]
Time complexity : O(n)
Space complexity: O(1)
Here is the ptyhon version
# This solution use O(n) time and O(n) space
def productExceptSelf(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
N = len(nums)
if N == 0: return
# Initialzie list of 1, size N
l_prods, r_prods = [1]*N, [1]*N
for i in range(1, N):
l_prods[i] = l_prods[i-1] * nums[i-1]
for i in reversed(range(N-1)):
r_prods[i] = r_prods[i+1] * nums[i+1]
result = [x*y for x,y in zip(l_prods,r_prods)]
return result
# This solution use O(n) time and O(1) space
def productExceptSelfSpaceOptimized(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
N = len(nums)
if N == 0: return
# Initialzie list of 1, size N
result = [1]*N
for i in range(1, N):
result[i] = result[i-1] * nums[i-1]
r_prod = 1
for i in reversed(range(N)):
result[i] *= r_prod
r_prod *= nums[i]
return result
{-
Recursive solution using sqrt(n) subsets. Runs in O(n).
Recursively computes the solution on sqrt(n) subsets of size sqrt(n).
Then recurses on the product sum of each subset.
Then for each element in each subset, it computes the product with
the product sum of all other products.
Then flattens all subsets.
Recurrence on the run time is T(n) = sqrt(n)*T(sqrt(n)) + T(sqrt(n)) + n
Suppose that T(n) ≤ cn in O(n).
T(n) = sqrt(n)*T(sqrt(n)) + T(sqrt(n)) + n
≤ sqrt(n)*c*sqrt(n) + c*sqrt(n) + n
≤ c*n + c*sqrt(n) + n
≤ (2c+1)*n
∈ O(n)
Note that ceiling(sqrt(n)) can be computed using a binary search
and O(logn) iterations, if the sqrt instruction is not permitted.
-}
otherProducts [] = []
otherProducts [x] = [1]
otherProducts [x,y] = [y,x]
otherProducts a = foldl' (++) [] $ zipWith (\s p -> map (*p) s) solvedSubsets subsetOtherProducts
where
n = length a
-- Subset size. Require that 1 < s < n.
s = ceiling $ sqrt $ fromIntegral n
solvedSubsets = map otherProducts subsets
subsetOtherProducts = otherProducts $ map product subsets
subsets = reverse $ loop a []
where loop [] acc = acc
loop a acc = loop (drop s a) ((take s a):acc)
To be complete here is the code in Scala:
val list1 = List(1, 2, 3, 4, 5)
for (elem <- list1) println(list1.filter(_ != elem) reduceLeft(_*_))
This will print out the following:
120
60
40
30
24
The program will filter out the current elem (_ != elem); and multiply the new list with reduceLeft method. I think this will be O(n) if you use scala view or Iterator for lazy eval.
Based on Billz answer--sorry I can't comment, but here is a scala version that correctly handles duplicate items in the list, and is probably O(n):
val list1 = List(1, 7, 3, 3, 4, 4)
val view = list1.view.zipWithIndex map { x => list1.view.patch(x._2, Nil, 1).reduceLeft(_*_)}
view.force
returns:
List(1008, 144, 336, 336, 252, 252)
Here is another simple concept which solves the problem in O(N).
int[] arr = new int[] {1, 2, 3, 4, 5};
int[] outArray = new int[arr.length];
for(int i=0;i<arr.length;i++){
int res=Arrays.stream(arr).reduce(1, (a, b) -> a * b);
outArray[i] = res/arr[i];
}
System.out.println(Arrays.toString(outArray));
Here's a slightly functional example, using C#:
Func<long>[] backwards = new Func<long>[input.Length];
Func<long>[] forwards = new Func<long>[input.Length];
for (int i = 0; i < input.Length; ++i)
{
var localIndex = i;
backwards[i] = () => (localIndex > 0 ? backwards[localIndex - 1]() : 1) * input[localIndex];
forwards[i] = () => (localIndex < input.Length - 1 ? forwards[localIndex + 1]() : 1) * input[localIndex];
}
var output = new long[input.Length];
for (int i = 0; i < input.Length; ++i)
{
if (0 == i)
{
output[i] = forwards[i + 1]();
}
else if (input.Length - 1 == i)
{
output[i] = backwards[i - 1]();
}
else
{
output[i] = forwards[i + 1]() * backwards[i - 1]();
}
}
I'm not entirely certain that this is O(n), due to the semi-recursion of the created Funcs, but my tests seem to indicate that it's O(n) in time.
My first try, in Python. O(2n):
def product(l):
product = 1
num_zeroes = 0
pos_zero = -1
# Multiply all and set positions
for i, x in enumerate(l):
if x != 0:
product *= x
l[i] = 1.0/x
else:
num_zeroes += 1
pos_zero = i
# Warning! Zeroes ahead!
if num_zeroes > 0:
l = [0] * len(l)
if num_zeroes == 1:
l[pos_zero] = product
else:
# Now set the definitive elements
for i in range(len(l)):
l[i] = int(l[i] * product)
return l
if __name__ == "__main__":
print("[0, 0, 4] = " + str(product([0, 0, 4])))
print("[3, 0, 4] = " + str(product([3, 0, 4])))
print("[1, 2, 3] = " + str(product([1, 2, 3])))
print("[2, 3, 4, 5, 6] = " + str(product([2, 3, 4, 5, 6])))
print("[2, 1, 2, 2, 3] = " + str(product([2, 1, 2, 2, 3])))
Output:
[0, 0, 4] = [0, 0, 0]
[3, 0, 4] = [0, 12, 0]
[1, 2, 3] = [6, 3, 2]
[2, 3, 4, 5, 6] = [360, 240, 180, 144, 120]
[2, 1, 2, 2, 3] = [12, 24, 12, 12, 8]
Here is my concise solution using python.
from functools import reduce
def excludeProductList(nums_):
after = [reduce(lambda x, y: x*y, nums_[i:]) for i in range(1, len(nums_))] + [1]
before = [1] + [reduce(lambda x, y: x*y, nums_[:i]) for i in range(1, len(nums_))]
zippedList = list(zip(before, after))
finalList = list(map(lambda x: x[0]*x[1], zippedList))
return finalList
We can exclude the nums[j] (where j != i) from list first, then get the product of the rest; The following is a python way to solve this puzzle:
from functools import reduce
def products(nums):
return [ reduce(lambda x,y: x * y, nums[:i] + nums[i+1:]) for i in range(len(nums)) ]
print(products([1, 2, 3, 4, 5]))
[out]
[120, 60, 40, 30, 24]
Here is a C implementation
O(n) time complexity.
INPUT
#include<stdio.h>
int main()
{
int x;
printf("Enter The Size of Array : ");
scanf("%d",&x);
int array[x-1],i ;
printf("Enter The Value of Array : \n");
for( i = 0 ; i <= x-1 ; i++)
{
printf("Array[%d] = ",i);
scanf("%d",&array[i]);
}
int left[x-1] , right[x-1];
left[0] = 1 ;
right[x-1] = 1 ;
for( i = 1 ; i <= x-1 ; i++)
{
left[i] = left[i-1] * array[i-1];
}
printf("\nThis is Multiplication of array[i-1] and left[i-1]\n");
for( i = 0 ; i <= x-1 ; i++)
{
printf("Array[%d] = %d , Left[%d] = %d\n",i,array[i],i,left[i]);
}
for( i = x-2 ; i >= 0 ; i--)
{
right[i] = right[i+1] * array[i+1];
}
printf("\nThis is Multiplication of array[i+1] and right[i+1]\n");
for( i = 0 ; i <= x-1 ; i++)
{
printf("Array[%d] = %d , Right[%d] = %d\n",i,array[i],i,right[i]);
}
printf("\nThis is Multiplication of Right[i] * Left[i]\n");
for( i = 0 ; i <= x-1 ; i++)
{
printf("Right[%d] * left[%d] = %d * %d = %d\n",i,i,right[i],left[i],right[i]*left[i]);
}
return 0 ;
}
Enter The Size of Array : 5
Enter The Value of Array :
Array[0] = 1
Array[1] = 2
Array[2] = 3
Array[3] = 4
Array[4] = 5
This is Multiplication of array[i-1] and left[i-1]
Array[0] = 1 , Left[0] = 1
Array[1] = 2 , Left[1] = 1
Array[2] = 3 , Left[2] = 2
Array[3] = 4 , Left[3] = 6
Array[4] = 5 , Left[4] = 24
This is Multiplication of array[i+1] and right[i+1]
Array[0] = 1 , Right[0] = 120
Array[1] = 2 , Right[1] = 60
Array[2] = 3 , Right[2] = 20
Array[3] = 4 , Right[3] = 5
Array[4] = 5 , Right[4] = 1
This is Multiplication of Right[i] * Left[i]
Right[0] * left[0] = 120 * 1 = 120
Right[1] * left[1] = 60 * 1 = 60
Right[2] * left[2] = 20 * 2 = 40
Right[3] * left[3] = 5 * 6 = 30
Right[4] * left[4] = 1 * 24 = 24
Process returned 0 (0x0) execution time : 6.548 s
Press any key to continue.
Try this!
import java.util.*;
class arrProduct
{
public static void main(String args[])
{
//getting the size of the array
Scanner s = new Scanner(System.in);
int noe = s.nextInt();
int out[]=new int[noe];
int arr[] = new int[noe];
// getting the input array
for(int k=0;k<noe;k++)
{
arr[k]=s.nextInt();
}
int val1 = 1,val2=1;
for(int i=0;i<noe;i++)
{
int res=1;
for(int j=1;j<noe;j++)
{
if((i+j)>(noe-1))
{
int diff = (i+j)-(noe);
if(arr[diff]!=0)
{
res = res * arr[diff];
}
}
else
{
if(arr[i+j]!=0)
{
res= res*arr[i+j];
}
}
out[i]=res;
}
}
//printing result
System.out.print("Array of Product: [");
for(int l=0;l<out.length;l++)
{
if(l!=out.length-1)
{
System.out.print(out[l]+",");
}
else
{
System.out.print(out[l]);
}
}
System.out.print("]");
}
}
Sneakily circumventing the "no divisions" rule:
sum = 0.0
for i in range(a):
sum += log(a[i])
for i in range(a):
output[i] = exp(sum - log(a[i]))
Here's a one-liner solution in Ruby.
nums.map { |n| (num - [n]).inject(:*) }
I got asked this question recently, and whilst I couldn't get O(N) during it, I had a different approach (unfortunately O(N^2)) but thought I'd share anyway.
Convert to List<Integer> first.
Loop through original array array.length() times.
Use a while loop to multiple the next set of required numbers:
while (temp < list.size() - 1) {
res *= list.get(temp);
temp++;
}
Then add res to a new array (which of course you've declared earlier), then add the value at array[i] to the List, and continue so forth.
I know this won't be of great use, but it's what I came up with under the pressures of an interview :)
int[] array = new int[]{1, 2, 3, 4, 5};
List<Integer> list = Arrays.stream(array).boxed().collect(Collectors.toList());
int[] newarray = new int[array.length];
int res = 1;
for (int i = 0; i < array.length; i++) {
int temp = i;
while (temp < list.size() - 1) {
res *= list.get(temp);
temp++;
}
newarray[i] = res;
list.add(array[i]);
res = 1;
}
Output: [24, 120, 60, 40, 30]
Here is a small recursive function (in C++) to do the modofication in place. It requires O(n) extra space (on stack) though. Assuming the array is in a and N holds the array length, we have
int multiply(int *a, int fwdProduct, int indx) {
int revProduct = 1;
if (indx < N) {
revProduct = multiply(a, fwdProduct*a[indx], indx+1);
int cur = a[indx];
a[indx] = fwdProduct * revProduct;
revProduct *= cur;
}
return revProduct;
}
public static void main(String[] args) {
int[] arr = { 1, 2, 3, 4, 5 };
int[] result = { 1, 1, 1, 1, 1 };
for (int i = 0; i < arr.length; i++) {
for (int j = 0; j < i; j++) {
result[i] *= arr[j];
}
for (int k = arr.length - 1; k > i; k--) {
result[i] *= arr[k];
}
}
for (int i : result) {
System.out.println(i);
}
}
This solution i came up with and i found it so clear what do you think!?
I have a solution with O(n) space and O(n^2) time complexity provided below,
public static int[] findEachElementAsProduct1(final int[] arr) {
int len = arr.length;
// int[] product = new int[len];
// Arrays.fill(product, 1);
int[] product = IntStream.generate(() -> 1).limit(len).toArray();
for (int i = 0; i < len; i++) {
for (int j = 0; j < len; j++) {
if (i == j) {
continue;
}
product[i] *= arr[j];
}
}
return product;
}
C++, O(n):
long long prod = accumulate(in.begin(), in.end(), 1LL, multiplies<int>());
transform(in.begin(), in.end(), back_inserter(res),
bind1st(divides<long long>(), prod));
Here you go, simple and clean solution with O(N) complexity:
int[] a = {1,2,3,4,5};
int[] r = new int[a.length];
int x = 1;
r[0] = 1;
for (int i=1;i<a.length;i++){
r[i]=r[i-1]*a[i-1];
}
for (int i=a.length-1;i>0;i--){
x=x*a[i];
r[i-1]=x*r[i-1];
}
for (int i=0;i<r.length;i++){
System.out.println(r[i]);
}
This is O(n^2) but f# is soooo beautiful:
List.fold (fun seed i -> List.mapi (fun j x -> if i=j+1 then x else x*i) seed)
[1;1;1;1;1]
[1..5]
Adding my javascript solution here as I didn't find anyone suggesting this. What is to divide, except to count the number of times you can extract a number from another number? I went through calculating the product of the whole array, and then iterate over each element, and substracting the current element until zero:
//No division operation allowed
// keep substracting divisor from dividend, until dividend is zero or less than divisor
function calculateProducsExceptCurrent_NoDivision(input){
var res = [];
var totalProduct = 1;
//calculate the total product
for(var i = 0; i < input.length; i++){
totalProduct = totalProduct * input[i];
}
//populate the result array by "dividing" each value
for(var i = 0; i < input.length; i++){
var timesSubstracted = 0;
var divisor = input[i];
var dividend = totalProduct;
while(divisor <= dividend){
dividend = dividend - divisor;
timesSubstracted++;
}
res.push(timesSubstracted);
}
return res;
}
There also is a O(N^(3/2)) non-optimal solution. It is quite interesting, though.
First preprocess each partial multiplications of size N^0.5(this is done in O(N) time complexity). Then, calculation for each number's other-values'-multiple can be done in 2*O(N^0.5) time(why? because you only need to multiple the last elements of other ((N^0.5) - 1) numbers, and multiply the result with ((N^0.5) - 1) numbers that belong to the group of the current number). Doing this for each number, one can get O(N^(3/2)) time.
Example:
4 6 7 2 3 1 9 5 8
partial results: 4*6*7 = 168 2*3*1 = 6 9*5*8 = 360
To calculate the value of 3, one needs to multiply the other groups' values 168*360, and then with 2*1.
I'm use to C#:
public int[] ProductExceptSelf(int[] nums)
{
int[] returnArray = new int[nums.Length];
List<int> auxList = new List<int>();
int multTotal = 0;
// If no zeros are contained in the array you only have to calculate it once
if(!nums.Contains(0))
{
multTotal = nums.ToList().Aggregate((a, b) => a * b);
for (int i = 0; i < nums.Length; i++)
{
returnArray[i] = multTotal / nums[i];
}
}
else
{
for (int i = 0; i < nums.Length; i++)
{
auxList = nums.ToList();
auxList.RemoveAt(i);
if (!auxList.Contains(0))
{
returnArray[i] = auxList.Aggregate((a, b) => a * b);
}
else
{
returnArray[i] = 0;
}
}
}
return returnArray;
}
// This is the recursive solution in Java // Called as following from main product(a,1,0);
public static double product(double[] a, double fwdprod, int index){
double revprod = 1;
if (index < a.length){
revprod = product2(a, fwdprod*a[index], index+1);
double cur = a[index];
a[index] = fwdprod * revprod;
revprod *= cur;
}
return revprod;
}
Precalculate the product of the numbers to the left and to the right of each element. For every element the desired value is the product of it's neigbors's products.
#include <stdio.h>
unsigned array[5] = { 1,2,3,4,5};
int main(void)
{
unsigned idx;
unsigned left[5]
, right[5];
left[0] = 1;
right[4] = 1;
/* calculate products of numbers to the left of [idx] */
for (idx=1; idx < 5; idx++) {
left[idx] = left[idx-1] * array[idx-1];
}
/* calculate products of numbers to the right of [idx] */
for (idx=4; idx-- > 0; ) {
right[idx] = right[idx+1] * array[idx+1];
}
for (idx=0; idx <5 ; idx++) {
printf("[%u] Product(%u*%u) = %u\n"
, idx, left[idx] , right[idx] , left[idx] * right[idx] );
}
return 0;
}
Result:
$ ./a.out
[0] Product(1*120) = 120
[1] Product(1*60) = 60
[2] Product(2*20) = 40
[3] Product(6*5) = 30
[4] Product(24*1) = 24
(UPDATE: now I look closer, this uses the same method as Michael Anderson, Daniel Migowski and polygenelubricants above)
int[] arr1 = { 1, 2, 3, 4, 5 };
int[] product = new int[arr1.Length];
for (int i = 0; i < arr1.Length; i++)
{
for (int j = 0; j < product.Length; j++)
{
if (i != j)
{
product[j] = product[j] == 0 ? arr1[i] : product[j] * arr1[i];
}
}
}
O(n)
ruby solution
a = [1,2,3,4]
result = []
a.each {|x| result.push( (a-[x]).reject(&:zero?).reduce(:*)) }
puts result
One more solution, Using division. with twice traversal. Multiply all the elements and then start dividing it by each element.
Here is my solution in modern C++. It makes use of std::transform and is pretty easy to remember.
#include<algorithm>
#include<iostream>
#include<vector>
using namespace std;
vector<int>& multiply_up(vector<int>& v){
v.insert(v.begin(),1);
transform(v.begin()+1, v.end()
,v.begin()
,v.begin()+1
,[](auto const& a, auto const& b) { return b*a; }
);
v.pop_back();
return v;
}
int main() {
vector<int> v = {1,2,3,4,5};
auto vr = v;
reverse(vr.begin(),vr.end());
multiply_up(v);
multiply_up(vr);
reverse(vr.begin(),vr.end());
transform(v.begin(),v.end()
,vr.begin()
,v.begin()
,[](auto const& a, auto const& b) { return b*a; }
);
for(auto& i: v) cout << i << " ";
}
A neat solution with O(n) runtime:
Create a final array "result", for an element i,
result[i] = pre[i-1]*post[i+1];
Translating Michael Anderson's solution into Haskell:
otherProducts xs = zipWith (*) below above
where below = scanl (*) 1 $ init xs
above = tail $ scanr (*) 1 xs
Just 2 passes up and down. Job done in O(N)
private static int[] multiply(int[] numbers) {
int[] multiplied = new int[numbers.length];
int total = 1;
multiplied[0] = 1;
for (int i = 1; i < numbers.length; i++) {
multiplied[i] = numbers[i - 1] * multiplied[i - 1];
}
for (int j = numbers.length - 2; j >= 0; j--) {
total *= numbers[j + 1];
multiplied[j] = total * multiplied[j];
}
return multiplied;
}
Tricky:
Use the following:
public int[] calc(int[] params) {
int[] left = new int[n-1]
in[] right = new int[n-1]
int fac1 = 1;
int fac2 = 1;
for( int i=0; i<n; i++ ) {
fac1 = fac1 * params[i];
fac2 = fac2 * params[n-i];
left[i] = fac1;
right[i] = fac2;
}
fac = 1;
int[] results = new int[n];
for( int i=0; i<n; i++ ) {
results[i] = left[i] * right[i];
}
Yes, I am sure i missed some i-1 instead of i, but thats the way to solve it.
Coded up using EcmaScript 2015
'use strict'
/*
Write a function that, given an array of n integers, returns an array of all possible products using exactly (n - 1) of those integers.
*/
/*
Correct behavior:
- the output array will have the same length as the input array, ie. one result array for each skipped element
- to compare result arrays properly, the arrays need to be sorted
- if array lemgth is zero, result is empty array
- if array length is 1, result is a single-element array of 1
input array: [1, 2, 3]
1*2 = 2
1*3 = 3
2*3 = 6
result: [2, 3, 6]
*/
class Test {
setInput(i) {
this.input = i
return this
}
setExpected(e) {
this.expected = e.sort()
return this
}
}
class FunctionTester {
constructor() {
this.tests = [
new Test().setInput([1, 2, 3]).setExpected([6, 3, 2]),
new Test().setInput([2, 3, 4, 5, 6]).setExpected([3 * 4 * 5 * 6, 2 * 4 * 5 * 6, 2 * 3 * 5 * 6, 2 * 3 * 4 * 6, 2 * 3 * 4 * 5]),
]
}
test(f) {
console.log('function:', f.name)
this.tests.forEach((test, index) => {
var heading = 'Test #' + index + ':'
var actual = f(test.input)
var failure = this._check(actual, test)
if (!failure) console.log(heading, 'input:', test.input, 'output:', actual)
else console.error(heading, failure)
return !failure
})
}
testChain(f) {
this.test(f)
return this
}
_check(actual, test) {
if (!Array.isArray(actual)) return 'BAD: actual not array'
if (actual.length !== test.expected.length) return 'BAD: actual length is ' + actual.length + ' expected: ' + test.expected.length
if (!actual.every(this._isNumber)) return 'BAD: some actual values are not of type number'
if (!actual.sort().every(isSame)) return 'BAD: arrays not the same: [' + actual.join(', ') + '] and [' + test.expected.join(', ') + ']'
function isSame(value, index) {
return value === test.expected[index]
}
}
_isNumber(v) {
return typeof v === 'number'
}
}
/*
Efficient: use two iterations of an aggregate product
We need two iterations, because one aggregate goes from last-to-first
The first iteration populates the array with products of indices higher than the skipped index
The second iteration calculates products of indices lower than the skipped index and multiplies the two aggregates
input array:
1 2 3
2*3
1* 3
1*2
input array:
2 3 4 5 6
(3 * 4 * 5 * 6)
(2) * 4 * 5 * 6
(2 * 3) * 5 * 6
(2 * 3 * 4) * (6)
(2 * 3 * 4 * 5)
big O: (n - 2) + (n - 2)+ (n - 2) = 3n - 6 => o(3n)
*/
function multiplier2(ns) {
var result = []
if (ns.length > 1) {
var lastIndex = ns.length - 1
var aggregate
// for the first iteration, there is nothing to do for the last element
var index = lastIndex
for (var i = 0; i < lastIndex; i++) {
if (!i) aggregate = ns[index]
else aggregate *= ns[index]
result[--index] = aggregate
}
// for second iteration, there is nothing to do for element 0
// aggregate does not require multiplication for element 1
// no multiplication is required for the last element
for (var i = 1; i <= lastIndex; i++) {
if (i === 1) aggregate = ns[0]
else aggregate *= ns[i - 1]
if (i !== lastIndex) result[i] *= aggregate
else result[i] = aggregate
}
} else if (ns.length === 1) result[0] = 1
return result
}
/*
Create the list of products by iterating over the input array
the for loop is iterated once for each input element: that is n
for every n, we make (n - 1) multiplications, that becomes n (n-1)
O(n^2)
*/
function multiplier(ns) {
var result = []
for (var i = 0; i < ns.length; i++) {
result.push(ns.reduce((reduce, value, index) =>
!i && index === 1 ? value // edge case: we should skip element 0 and it's the first invocation: ignore reduce
: index !== i ? reduce * value // multiply if it is not the element that should be skipped
: reduce))
}
return result
}
/*
Multiply by clone the array and remove one of the integers
O(n^2) and expensive array manipulation
*/
function multiplier0(ns) {
var result = []
for (var i = 0; i < ns.length; i++) {
var ns1 = ns.slice() // clone ns array
ns1.splice(i, 1) // remove element i
result.push(ns1.reduce((reduce, value) => reduce * value))
}
return result
}
new FunctionTester().testChain(multiplier0).testChain(multiplier).testChain(multiplier2)
run with Node.js v4.4.5 like:
node --harmony integerarrays.js
function: multiplier0
Test #0: input: [ 1, 2, 3 ] output: [ 2, 3, 6 ]
Test #1: input: [ 2, 3, 4, 5, 6 ] output: [ 120, 144, 180, 240, 360 ]
function: multiplier
Test #0: input: [ 1, 2, 3 ] output: [ 2, 3, 6 ]
Test #1: input: [ 2, 3, 4, 5, 6 ] output: [ 120, 144, 180, 240, 360 ]
function: multiplier2
Test #0: input: [ 1, 2, 3 ] output: [ 2, 3, 6 ]
Test #1: input: [ 2, 3, 4, 5, 6 ] output: [ 120, 144, 180, 240, 360 ]
I came up with 2 solutions in Javascript, one with division and one without
// without division
function methodOne(arr) {
return arr.map(item => {
return arr.reduce((result, num) => {
if (num !== item) {
result = result * num;
}
return result;
},1)
});
}
// with division
function methodTwo(arr) {
var mul = arr.reduce((result, num) => {
result = result * num;
return result;
},1)
return arr.map(item => mul/item);
}
console.log(methodOne([1, 2, 3, 4, 5]));
console.log(methodTwo([1, 2, 3, 4, 5]));Source: Stackoverflow.com