原文链接: https://leetcode-cn.com/problems/3sum-with-multiplicity
英文原文
Given an integer array arr
, and an integer target
, return the number of tuples i, j, k
such that i < j < k
and arr[i] + arr[j] + arr[k] == target
.
As the answer can be very large, return it modulo 109 + 7
.
Example 1:
Input: arr = [1,1,2,2,3,3,4,4,5,5], target = 8 Output: 20 Explanation: Enumerating by the values (arr[i], arr[j], arr[k]): (1, 2, 5) occurs 8 times; (1, 3, 4) occurs 8 times; (2, 2, 4) occurs 2 times; (2, 3, 3) occurs 2 times.
Example 2:
Input: arr = [1,1,2,2,2,2], target = 5 Output: 12 Explanation: arr[i] = 1, arr[j] = arr[k] = 2 occurs 12 times: We choose one 1 from [1,1] in 2 ways, and two 2s from [2,2,2,2] in 6 ways.
Constraints:
3 <= arr.length <= 3000
0 <= arr[i] <= 100
0 <= target <= 300
中文题目
给定一个整数数组 A
,以及一个整数 target
作为目标值,返回满足 i < j < k
且 A[i] + A[j] + A[k] == target
的元组 i, j, k
的数量。
由于结果会非常大,请返回 结果除以 10^9 + 7 的余数
。
示例 1:
输入:A = [1,1,2,2,3,3,4,4,5,5], target = 8 输出:20 解释: 按值枚举(A[i],A[j],A[k]): (1, 2, 5) 出现 8 次; (1, 3, 4) 出现 8 次; (2, 2, 4) 出现 2 次; (2, 3, 3) 出现 2 次。
示例 2:
输入:A = [1,1,2,2,2,2], target = 5 输出:12 解释: A[i] = 1,A[j] = A[k] = 2 出现 12 次: 我们从 [1,1] 中选择一个 1,有 2 种情况, 从 [2,2,2,2] 中选出两个 2,有 6 种情况。
提示:
3 <= A.length <= 3000
0 <= A[i] <= 100
0 <= target <= 300
通过代码
官方题解
方法须知
下面讲的方法跟用双指针来做 "两数之和"
有异曲同工之妙,先来看一下 "两数之和"
这道题。
假设有一个有序数组,同时这个数组中元素唯一,想知道有多少对 i
,j
,满足 i < j
且 A[i] + A[j] == target
。
"两数之和"
可以在线性时间解决的,定义两个指针 i
,j
,初始分别指向数组的头尾,i
逐渐递增,j
逐渐递减,来找出所有满足 A[i] + A[j] == target
的组合。
def solve(A, target):
# Assume A already sorted
i, j = 0, len(A) - 1
ans = 0
while i < j:
if A[i] + A[j] < target:
i += 1
elif A[i] + A[j] > target:
j -= 1
else:
ans += 1
i += 1
j -= 1
return ans
方法一: 三指针
思路和算法
先将数组进行排序,遍历数组下标,对于每个 i
,设 T = target - A[i]
作为剩余要凑成的目标数。接着用双指针来完成 A[j] + A[k] == T
的子任务。
考虑到有些元素是重复的,需要小心处理边界条件。在特殊的情况下,比如说 target = 8
,数组为 [2,2,2,2,3,3,4,4,4,5,5,5,6,6]
,这个数组就有大量的重复元素可以组成 target
,下面来分析一下这种情况该怎么处理。
只要 A[j] + A[k] == T
,就要算上这一对 j
, k
组合。在这个例子里面,当 A[j] == 2
,A[k] == 6
,有 4 * 2 = 8
种组合方式。
在特殊情况下,如果 A[j] == A[k]
,比如最后剩下的 [4,4,4]
,这里有 3
对。一般情况下,如果 A[j] == A[k]
,我们有 $\binom{M}{2} = \frac{M*(M-1)}{2}$ 对 (j,k)
(满足 j < k
且 A[j] + A[k] == T
)。
class Solution {
public int threeSumMulti(int[] A, int target) {
int MOD = 1_000_000_007;
long ans = 0;
Arrays.sort(A);
for (int i = 0; i < A.length; ++i) {
// We'll try to find the number of i < j < k
// with A[j] + A[k] == T, where T = target - A[i].
// The below is a "two sum with multiplicity".
int T = target - A[i];
int j = i+1, k = A.length - 1;
while (j < k) {
// These steps proceed as in a typical two-sum.
if (A[j] + A[k] < T)
j++;
else if (A[j] + A[k] > T)
k--;
else if (A[j] != A[k]) { // We have A[j] + A[k] == T.
// Let's count "left": the number of A[j] == A[j+1] == A[j+2] == ...
// And similarly for "right".
int left = 1, right = 1;
while (j+1 < k && A[j] == A[j+1]) {
left++;
j++;
}
while (k-1 > j && A[k] == A[k-1]) {
right++;
k--;
}
ans += left * right;
ans %= MOD;
j++;
k--;
} else {
// M = k - j + 1
// We contributed M * (M-1) / 2 pairs.
ans += (k-j+1) * (k-j) / 2;
ans %= MOD;
break;
}
}
}
return (int) ans;
}
}
class Solution(object):
def threeSumMulti(self, A, target):
MOD = 10**9 + 7
ans = 0
A.sort()
for i, x in enumerate(A):
# We'll try to find the number of i < j < k
# with A[j] + A[k] == T, where T = target - A[i].
# The below is a "two sum with multiplicity".
T = target - A[i]
j, k = i+1, len(A) - 1
while j < k:
# These steps proceed as in a typical two-sum.
if A[j] + A[k] < T:
j += 1
elif A[j] + A[k] > T:
k -= 1
# These steps differ:
elif A[j] != A[k]: # We have A[j] + A[k] == T.
# Let's count "left": the number of A[j] == A[j+1] == A[j+2] == ...
# And similarly for "right".
left = right = 1
while j + 1 < k and A[j] == A[j+1]:
left += 1
j += 1
while k - 1 > j and A[k] == A[k-1]:
right += 1
k -= 1
# We contributed left * right many pairs.
ans += left * right
ans %= MOD
j += 1
k -= 1
else:
# M = k - j + 1
# We contributed M * (M-1) / 2 pairs.
ans += (k-j+1) * (k-j) / 2
ans %= MOD
break
return ans
复杂度分析
时间复杂度: $O(N^2)$,其中 $N$ 为
A
的长度。空间复杂度: $O(1)$。
方法二: 数学法
思路和算法
设 count[x]
为数组 A
中 x
出现的次数。对于每种 x+y+z == target
,可以数一下有多少种可能的组合,这里可以看几个例子:
如果
x
,y
,z
各不相同,有count[x] * count[y] * count[z]
中组合。如果
x == y != z
,有 $\binom{\text{count[x]}}{2} * \text{count[z]}$ 种组合。如果
x != y == z
,有 $\text{count[x]} * \binom{\text{count[y]}}{2}$ 种组合。如果
x == y == z
,有 $\binom{\text{count[x]}}{3}$ 中组合。
($\binom{n}{k}$ 表示二项式系数 $\frac{n!}{(n-k)!k!}$.)
class Solution {
public int threeSumMulti(int[] A, int target) {
int MOD = 1_000_000_007;
long[] count = new long[101];
for (int x: A)
count[x]++;
long ans = 0;
// All different
for (int x = 0; x <= 100; ++x)
for (int y = x+1; y <= 100; ++y) {
int z = target - x - y;
if (y < z && z <= 100) {
ans += count[x] * count[y] * count[z];
ans %= MOD;
}
}
// x == y != z
for (int x = 0; x <= 100; ++x) {
int z = target - 2*x;
if (x < z && z <= 100) {
ans += count[x] * (count[x] - 1) / 2 * count[z];
ans %= MOD;
}
}
// x != y == z
for (int x = 0; x <= 100; ++x) {
if (target % 2 == x % 2) {
int y = (target - x) / 2;
if (x < y && y <= 100) {
ans += count[x] * count[y] * (count[y] - 1) / 2;
ans %= MOD;
}
}
}
// x == y == z
if (target % 3 == 0) {
int x = target / 3;
if (0 <= x && x <= 100) {
ans += count[x] * (count[x] - 1) * (count[x] - 2) / 6;
ans %= MOD;
}
}
return (int) ans;
}
}
class Solution(object):
def threeSumMulti(self, A, target):
MOD = 10**9 + 7
count = [0] * 101
for x in A:
count[x] += 1
ans = 0
# All different
for x in xrange(101):
for y in xrange(x+1, 101):
z = target - x - y
if y < z <= 100:
ans += count[x] * count[y] * count[z]
ans %= MOD
# x == y
for x in xrange(101):
z = target - 2*x
if x < z <= 100:
ans += count[x] * (count[x] - 1) / 2 * count[z]
ans %= MOD
# y == z
for x in xrange(101):
if (target - x) % 2 == 0:
y = (target - x) / 2
if x < y <= 100:
ans += count[x] * count[y] * (count[y] - 1) / 2
ans %= MOD
# x == y == z
if target % 3 == 0:
x = target / 3
if 0 <= x <= 100:
ans += count[x] * (count[x] - 1) * (count[x] - 2) / 6
ans %= MOD
return ans
复杂度分析
时间复杂度: $O(N + W^2)$,其中 $N$ 为
A
的长度,$W$ 为A[i]
中最大的数。空间复杂度: $O(W)$。
方法三: 变种的三数之和
思路和算法那
在 方法二 中,count[x]
为 A
中 x
出现的次数。同时,让 keys
为数组 A
中所有元素只出现一次的有序数组。接着用三数之和的方法来处理 keys
。
举个例子,如果 A = [1,1,2,2,3,3,4,4,5,5]
,target = 8
,得到 keys = [1,2,3,4,5]
。当对 keys
做三数之和的时候,会遇到一些组合使得三数相加为 target
,比如 (x,y,z) = (1,2,5), (1,3,4), (2,2,4), (2,3,3)
。接着用 count
来算每种组合有多少次。
class Solution {
public int threeSumMulti(int[] A, int target) {
int MOD = 1_000_000_007;
// Initializing as long saves us the trouble of
// managing count[x] * count[y] * count[z] overflowing later.
long[] count = new long[101];
int uniq = 0;
for (int x: A) {
count[x]++;
if (count[x] == 1)
uniq++;
}
int[] keys = new int[uniq];
int t = 0;
for (int i = 0; i <= 100; ++i)
if (count[i] > 0)
keys[t++] = i;
long ans = 0;
// Now, let's do a 3sum on "keys", for i <= j <= k.
// We will use count to add the correct contribution to ans.
for (int i = 0; i < keys.length; ++i) {
int x = keys[i];
int T = target - x;
int j = i, k = keys.length - 1;
while (j <= k) {
int y = keys[j], z = keys[k];
if (y + z < T) {
j++;
} else if (y + z > T) {
k--;
} else { // # x+y+z == T, now calc the size of the contribution
if (i < j && j < k) {
ans += count[x] * count[y] * count[z];
} else if (i == j && j < k) {
ans += count[x] * (count[x] - 1) / 2 * count[z];
} else if (i < j && j == k) {
ans += count[x] * count[y] * (count[y] - 1) / 2;
} else { // i == j == k
ans += count[x] * (count[x] - 1) * (count[x] - 2) / 6;
}
ans %= MOD;
j++;
k--;
}
}
}
return (int) ans;
}
}
class Solution(object):
def threeSumMulti(self, A, target):
MOD = 10**9 + 7
count = collections.Counter(A)
keys = sorted(count)
ans = 0
# Now, let's do a 3sum on "keys", for i <= j <= k.
# We will use count to add the correct contribution to ans.
for i, x in enumerate(keys):
T = target - x
j, k = i, len(keys) - 1
while j <= k:
y, z = keys[j], keys[k]
if y + z < T:
j += 1
elif y + z > T:
k -= 1
else: # x+y+z == T, now calculate the size of the contribution
if i < j < k:
ans += count[x] * count[y] * count[z]
elif i == j < k:
ans += count[x] * (count[x] - 1) / 2 * count[z]
elif i < j == k:
ans += count[x] * count[y] * (count[y] - 1) / 2
else: # i == j == k
ans += count[x] * (count[x] - 1) * (count[x] - 2) / 6
j += 1
k -= 1
return ans % MOD
复杂度分析
时间复杂度: $O(N^2)$,其中 $N$ 是
A
的长度。空间复杂度: $O(N)$。
统计信息
通过次数 | 提交次数 | AC比率 |
---|---|---|
6587 | 19268 | 34.2% |
提交历史
提交时间 | 提交结果 | 执行时间 | 内存消耗 | 语言 |
---|