Reputation: 143
The Magical Sequence
A Magical Sequence is defined as shown.
Magical[1] = 0
Magical[2] = 1
Magical[n] = Magical[n-1] + 2*Magical[n-2] + 3*Magical[n-3] + ... (n-1)*Magical[1] + n*1., for n > 2
Given n (1 <= n <= 10^9 )
, find Magical[n].
Example 1: input: 3 Output: 4
Explanation:
Magical[n] = 1*Magical[n-1] + 2*Magical[n-2] + 3*1
Magical[3] = 1*Magical[2] + 2*Magical[1] + 3*1
Magical[3] = 1*1 + 2*0 + 3*1
Magical[3] = 4
Example 2: input: 4 Output: 10
Magical[4] = 1*Magical[3]+2*Magical[2]+3*Magical[1]+4*1
= 1*4+2*1+3*0+4 = 10
Example 3: input: 5 Output: 26
Magical[5] = 1*Magical[4]+2*Magical[3]+3*Magical[2]+4*Magical[1]+5*1
= 1*10+2*4+3*1+4*0+5 = 26
I tried something like below :-
int CuckooNum(int n)
{
if (1 == n)
{
return 0;
}
else if (2 == n)
{
return 1;
}
std::vector<int> vec;
vec.resize(n);
vec[0] = 4;
vec[1] = 0;
vec[2] = 1;
int multiplyer = n;
int result = 0;
for (int index=3; index <= n; index++)
{
result += multiplyer * vec[index-1];
vec[index] = result;
multiplyer--;
}
return result;
}
Upvotes: 1
Views: 269
Reputation: 4864
As the size n
can be very large (10^9), a direct implementation O(n^2) is not possible.
A specific algorithm is needed. I will focus here on the algorithm, and propose a O(log n) solution.
To simplify explanation, I rename magical[]
as x[]
Moreover, we can define x[0] = 1
. Then,
x[n] = x[n-1] + 2*x[n-2] + 3*x[n-3] + ... (n-1)*x[1] + n*x[0]
As
x[n-1] = 1*x[n-2] + 2*x[n-3] + ... (n-2)*x[1] + (n-1)*x[0]
It follows
x[n] - x[n-1] = x[n-1] + x[n-2] + x[n-3] + ... x[1] + x[0] = S[n-1]
When S[n]
represents the sum of the terms until n
(x[0]
included)
Moreover,
S[n] = S[n-1] + x[n] = 2*S[n-1] + x[n-1]
Therefore, the iterative formula can be represented in a simple matrix form:
(x[n]) = (1 1) (x[n-1])
(S[n]) (1 2) (S[n-1])
Or, defining the vector (x[n] S[n])^t as Z[n]:
Z[n] = A * Z[n-1] where A is the matrix (1 1)
(1 2)
Note: this formula is valid for n>= 4
only, as the first x[n]
values do no respect the simple recurrence relation.
It follows that
Z[n] = A^(n-3) Z[3] with Z[3] = (4 6)^t
Classically, this calculation can be performed with O(log n) complexity, iteratively calculating A^2, A^4, A^8
etc.
Pay attention that the values increase rapidly.
Here is an example of C++ implementation. Note that this implementation is not optimized, as for example it doesn't use the fact that all matrices are symmetric.
#include <iostream>
#include <array>
using Matr22 = std::array<std::array<long long int, 2>, 2>;
using Vect2 = std::array<long long int, 2>;
Matr22 Matrsquare (const Matr22 &m) {
Matr22 m2;
m2[0][0] = m[0][0]*m[0][0] + m[0][1]*m[1][0];
m2[0][1] = m[0][0]*m[0][1] + m[0][1]*m[1][1];
m2[1][0] = m[1][0]*m[0][0] + m[1][1]*m[1][0];
m2[1][1] = m[1][0]*m[0][1] + m[1][1]*m[1][1];
return m2;
}
Matr22 Mult (const Matr22 &m1, const Matr22 &m2) {
Matr22 y;
y[0][0] = m1[0][0]*m2[0][0] + m1[0][1]*m2[1][0];
y[0][1] = m1[0][0]*m2[0][1] + m1[0][1]*m2[1][1];
y[1][0] = m1[1][0]*m2[0][0] + m1[1][1]*m2[1][0];
y[1][1] = m1[1][0]*m2[0][1] + m1[1][1]*m2[1][1];
return y;
}
Vect2 Mult (const Matr22 &m, const Vect2& x) {
Vect2 y;
y[0] = m[0][0] * x[0] + m[0][1] * x[1];
y[1] = m[1][0] * x[0] + m[1][1] * x[1];
return y;
}
// Matrix exponentiation
Matr22 Mult_exp (const Matr22 &m, int exp) {
Matr22 y = {1, 0, 0, 1};
if (exp == 0) return y;
Matr22 M2k = m;
while (exp) {
if (exp%2) y = Mult (y, M2k);
M2k = Matrsquare (M2k);
exp /= 2;
};
return y;
}
long long int Magical (int n) {
if (n == 1) return 0;
if (n == 2) return 1;
if (n == 3) return 4;
Matr22 A = {1, 1, 1, 2};
Vect2 z = {4, 6}; // corresponds to n=3
auto Ak = Mult_exp (A, n-3);
z = Mult (Ak, z);
return z[0];
}
int main() {
int n;
std::cout << "Input n: ";
std::cin >> n;
auto ans = Magical (n);
std::cout << "Magical[" << n << "] = " << ans << '\n';
}
Upvotes: 1
Reputation: 158
long long func(int n)
{
if (n==1) return 0;
else if (n==2) return 1;
else return 1*func(n-1)+2*func(n-2)+n;
}
Upvotes: 2