Description#
You are given a 2D integer array, queries
. For each queries[i]
, where queries[i] = [ni, ki]
, find the number of different ways you can place positive integers into an array of size ni
such that the product of the integers is ki
. As the number of ways may be too large, the answer to the ith
query is the number of ways modulo 109 + 7
.
Return an integer array answer
where answer.length == queries.length
, and answer[i]
is the answer to the ith
query.
Example 1:
Input: queries = [[2,6],[5,1],[73,660]]
Output: [4,1,50734910]
Explanation: Each query is independent.
[2,6]: There are 4 ways to fill an array of size 2 that multiply to 6: [1,6], [2,3], [3,2], [6,1].
[5,1]: There is 1 way to fill an array of size 5 that multiply to 1: [1,1,1,1,1].
[73,660]: There are 1050734917 ways to fill an array of size 73 that multiply to 660. 1050734917 modulo 109 + 7 = 50734910.
Example 2:
Input: queries = [[1,1],[2,2],[3,3],[4,4],[5,5]]
Output: [1,2,3,10,5]
Constraints:
1 <= queries.length <= 104
1 <= ni, ki <= 104
Solutions#
Solution 1: Prime Factorization + Combinatorial Mathematics#
We can perform prime factorization on $k$, i.e., $k = p_1^{x_1} \times p_2^{x_2} \times \cdots \times p_m^{x_m}$, where $p_i$ is a prime number, and $x_i$ is the exponent of $p_i$. The problem is equivalent to: placing $x_1$ $p_1$s, $x_2$ $p_2$s, $\cdots$, $x_m$ $p_m$s into $n$ positions respectively, where a single position can be empty. The question is how many schemes are there.
According to combinatorial mathematics, there are two cases when we put $x$ balls into $n$ boxes:
If the box cannot be empty, the number of schemes is $C_{x-1}^{n-1}$. This is using the partition method, i.e., there are a total of $x$ balls, and we insert $n-1$ partitions at $x-1$ positions, thereby dividing the $x$ balls into $n$ groups.
If the box can be empty, we can add $n$ virtual balls, and then use the partition method, i.e., there are a total of $x+n$ balls, and we insert $n-1$ partitions at $x+n-1$ positions, thereby dividing the actual $x$ balls into $n$ groups and allowing the box to be empty. Therefore, the number of schemes is $C_{x+n-1}^{n-1}$.
Therefore, for each query $queries[i]$, we can first perform prime factorization on $k$ to get the exponents $x_1, x_2, \cdots, x_m$, then calculate $C_{x_1+n-1}^{n-1}, C_{x_2+n-1}^{n-1}, \cdots, C_{x_m+n-1}^{n-1}$, and finally multiply all the scheme numbers.
So, the problem is transformed into how to quickly calculate $C_m^n$. According to the formula $C_m^n = \frac{m!}{n!(m-n)!}$, we can pre-process $m!$, and then use the inverse element to quickly calculate $C_m^n$.
The time complexity is $O(K \times \log \log K + N + m \times \log K)$, and the space complexity is $O(N)$.
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| N = 10020
MOD = 10**9 + 7
f = [1] * N
g = [1] * N
p = defaultdict(list)
for i in range(1, N):
f[i] = f[i - 1] * i % MOD
g[i] = pow(f[i], MOD - 2, MOD)
x = i
j = 2
while j <= x // j:
if x % j == 0:
cnt = 0
while x % j == 0:
cnt += 1
x //= j
p[i].append(cnt)
j += 1
if x > 1:
p[i].append(1)
def comb(n, k):
return f[n] * g[k] * g[n - k] % MOD
class Solution:
def waysToFillArray(self, queries: List[List[int]]) -> List[int]:
ans = []
for n, k in queries:
t = 1
for x in p[k]:
t = t * comb(x + n - 1, n - 1) % MOD
ans.append(t)
return ans
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| class Solution {
private static final int N = 10020;
private static final int MOD = (int) 1e9 + 7;
private static final long[] F = new long[N];
private static final long[] G = new long[N];
private static final List<Integer>[] P = new List[N];
static {
F[0] = 1;
G[0] = 1;
Arrays.setAll(P, k -> new ArrayList<>());
for (int i = 1; i < N; ++i) {
F[i] = F[i - 1] * i % MOD;
G[i] = qmi(F[i], MOD - 2, MOD);
int x = i;
for (int j = 2; j <= x / j; ++j) {
if (x % j == 0) {
int cnt = 0;
while (x % j == 0) {
++cnt;
x /= j;
}
P[i].add(cnt);
}
}
if (x > 1) {
P[i].add(1);
}
}
}
public static long qmi(long a, long k, long p) {
long res = 1;
while (k != 0) {
if ((k & 1) == 1) {
res = res * a % p;
}
k >>= 1;
a = a * a % p;
}
return res;
}
public static long comb(int n, int k) {
return (F[n] * G[k] % MOD) * G[n - k] % MOD;
}
public int[] waysToFillArray(int[][] queries) {
int m = queries.length;
int[] ans = new int[m];
for (int i = 0; i < m; ++i) {
int n = queries[i][0], k = queries[i][1];
long t = 1;
for (int x : P[k]) {
t = t * comb(x + n - 1, n - 1) % MOD;
}
ans[i] = (int) t;
}
return ans;
}
}
|
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| int N = 10020;
int MOD = 1e9 + 7;
long f[10020];
long g[10020];
vector<int> p[10020];
long qmi(long a, long k, long p) {
long res = 1;
while (k != 0) {
if ((k & 1) == 1) {
res = res * a % p;
}
k >>= 1;
a = a * a % p;
}
return res;
}
int init = []() {
f[0] = 1;
g[0] = 1;
for (int i = 1; i < N; ++i) {
f[i] = f[i - 1] * i % MOD;
g[i] = qmi(f[i], MOD - 2, MOD);
int x = i;
for (int j = 2; j <= x / j; ++j) {
if (x % j == 0) {
int cnt = 0;
while (x % j == 0) {
++cnt;
x /= j;
}
p[i].push_back(cnt);
}
}
if (x > 1) {
p[i].push_back(1);
}
}
return 0;
}();
int comb(int n, int k) {
return (f[n] * g[k] % MOD) * g[n - k] % MOD;
}
class Solution {
public:
vector<int> waysToFillArray(vector<vector<int>>& queries) {
vector<int> ans;
for (auto& q : queries) {
int n = q[0], k = q[1];
long long t = 1;
for (int x : p[k]) {
t = t * comb(x + n - 1, n - 1) % MOD;
}
ans.push_back(t);
}
return ans;
}
};
|
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| const n = 1e4 + 20
const mod = 1e9 + 7
var f = make([]int, n)
var g = make([]int, n)
var p = make([][]int, n)
func qmi(a, k, p int) int {
res := 1
for k != 0 {
if k&1 == 1 {
res = res * a % p
}
k >>= 1
a = a * a % p
}
return res
}
func init() {
f[0], g[0] = 1, 1
for i := 1; i < n; i++ {
f[i] = f[i-1] * i % mod
g[i] = qmi(f[i], mod-2, mod)
x := i
for j := 2; j <= x/j; j++ {
if x%j == 0 {
cnt := 0
for x%j == 0 {
cnt++
x /= j
}
p[i] = append(p[i], cnt)
}
}
if x > 1 {
p[i] = append(p[i], 1)
}
}
}
func comb(n, k int) int {
return (f[n] * g[k] % mod) * g[n-k] % mod
}
func waysToFillArray(queries [][]int) (ans []int) {
for _, q := range queries {
n, k := q[0], q[1]
t := 1
for _, x := range p[k] {
t = t * comb(x+n-1, n-1) % mod
}
ans = append(ans, t)
}
return
}
|