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.
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]"
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];
}
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];
}
}
}
An explaination of polygenelubricants method is: The trick is to construct the arrays (in the case for 4 elements)
{ 1, a[0], a[0]*a[1], a[0]*a[1]*a[2], }
{ a[1]*a[2]*a[3], a[2]*a[3], a[3], 1, }
Both of which can be done in O(n) by starting at the left and right edges respectively.
Then multiplying the two arrays element by element gives the required result
My code would look something like this:
int a[N] // This is the input
int products_below[N];
p=1;
for(int i=0;i<N;++i)
{
products_below[i]=p;
p*=a[i];
}
int products_above[N];
p=1;
for(int i=N-1;i>=0;--i)
{
products_above[i]=p;
p*=a[i];
}
int products[N]; // This is the result
for(int i=0;i<N;++i)
{
products[i]=products_below[i]*products_above[i];
}
If you need to be O(1) in space too you can do this (which is less clear IMHO)
int a[N] // This is the input
int products[N];
// Get the products below the curent index
p=1;
for(int i=0;i<N;++i)
{
products[i]=p;
p*=a[i];
}
// Get the products above the curent index
p=1;
for(int i=N-1;i>=0;--i)
{
products[i]*=p;
p*=a[i];
}
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.
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));
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]
Translating Michael Anderson's solution into Haskell:
otherProducts xs = zipWith (*) below above
where below = scanl (*) 1 $ init xs
above = tail $ scanr (*) 1 xs
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;
}
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]))
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.
One more solution, Using division. with twice traversal. Multiply all the elements and then start dividing it by each element.