我在一次工作面试中被问到这个问题,我想知道其他人是如何解决这个问题的。我最擅长使用Java,但也欢迎使用其他语言的解决方案。

给定一个数字数组nums,返回一个数字数组products,其中products[i]是所有nums[j]的乘积,j != i。 输入:[1,2,3,4,5] 输出:[(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] 你必须在O(N)中不使用除法来做这个。


当前回答

{-
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)

其他回答

给你,简单干净的解决方案,复杂度为O(N):

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]);
    }

ruby的解决方案

a = [1,2,3,4]
result = []
a.each {|x| result.push( (a-[x]).reject(&:zero?).reduce(:*)) }
puts result

我的第一次尝试,用Python。O (2 n):

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])))

输出:

[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]

鬼鬼祟祟地绕过“不划分”规则:

sum = 0.0
for i in range(a):
  sum += log(a[i])

for i in range(a):
  output[i] = exp(sum - log(a[i]))

技巧:

使用以下方法:

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];
}

是的,我确定我错过了一些I -1而不是I,但这是解决它的方法。