The whole thing about this polynomial time is confusing to me for example: I want to write a program in a polynomial time algorithm that will just pick only 4 integers that sum to 0 from a set.
For instance: Let assume I have the following set of integers {8, 20, 3, -2, 3, 7, 16, -9}. How can I pick only 4 distinct integers that sum to 0 from a set in polynomial time without having needed to check through every possible length other than 4? Note in the program I don’t need to search through any other possible length than 4. My expected solution is {8, 3, -2, -9} = 0. knowing fully well that i only need 4 integers from the set {8, 20, 3, -2, 3, 7, 16, -9}.
Edit: Will I found a polynomial time solution of {8, 3, -2, -9} even if I increase only the length of the original set from 8 to 100 integers while I will still have to pick my 4 elements that sum to 0 but from the set of 100 integers will it still be polynomial fast with respect to the size of the input (i.e the number of bits used to store the input)?
The following algorithm runs in O(N^3 * logN).
#include <algorithm>
#include <iostream>
#include <tuple>
#include <vector>
using quadruple = std::tuple<int, int, int, int>;
std::vector<quadruple> find(std::vector<int> vec) {
std::sort(vec.begin(), vec.end());
vec.erase(std::unique(vec.begin(), vec.end()), vec.end());
std::vector<quadruple> ret;
for (auto i = 0u; i + 3 < vec.size(); ++i) {
for (auto j = i + 1; j + 2 < vec.size(); ++j) {
for (auto k = j + 1; k + 1 < vec.size(); ++k) {
auto target = 0 - vec[i] - vec[j] - vec[k];
auto it = std::lower_bound(vec.begin() + k + 1,
vec.end(),
target);
if (it != vec.end() && *it == target) {
ret.push_back(std::make_tuple(
vec[i], vec[j], vec[k], target));
}
}
}
}
return ret;
}
int main() {
std::vector<int> input = {8, 20, 3, -2, 3, 7, 16, -9};
auto output = find(input);
for (auto& quad : output) {
std::cout << std::get<0>(quad) << ' '
<< std::get<1>(quad) << ' '
<< std::get<2>(quad) << ' '
<< std::get<3>(quad) << std::endl;
}
}
Try all quadruples without repetitions. This takes at most (N^4-6N³+11N²-6N)/24 attempts each made in constant time.
8 + 20 + 3 - 2 = 29
8 + 20 + 3 + 3 = 34
8 + 20 + 3 + 7 = 38
8 + 20 + 3 + 16 = 47
8 + 20 + 3 - 9 = 22
8 + 20 - 2 + 3 = 29
8 + 20 - 2 + 7 = 33
8 + 20 - 2 + 16 = 42
8 + 20 - 2 - 9 = 17
8 + 20 + 3 + 7 = 38
8 + 20 + 3 + 16 = 47
8 + 20 + 3 - 9 = 22
8 + 20 + 7 + 16 = 51
8 + 20 + 7 - 9 = 26
8 + 20 + 16 - 9 = 35
8 + 3 - 2 + 3 = 12
8 + 3 - 2 + 7 = 16
8 + 3 - 2 + 16 = 25
8 + 3 - 2 - 9 = 0 <==
8 + 3 + 3 + 7 = 21
8 + 3 + 3 + 16 = 30
8 + 3 + 3 - 9 = 5
8 + 3 + 7 + 16 = 34
8 + 3 + 7 - 9 = 9
8 + 3 + 16 - 9 = 18
8 - 2 + 3 + 7 = 16
8 - 2 + 3 + 16 = 25
8 - 2 + 3 - 9 = 0 <==
8 - 2 + 7 + 16 = 29
8 - 2 + 7 - 9 = 4
8 - 2 + 16 - 9 = 13
8 + 3 + 7 + 16 = 34
8 + 3 + 7 - 9 = 9
8 + 3 + 16 - 9 = 18
8 + 7 + 16 - 9 = 22
20 + 3 - 2 + 3 = 24
20 + 3 - 2 + 7 = 28
20 + 3 - 2 + 16 = 37
20 + 3 - 2 - 9 = 12
20 + 3 + 3 + 7 = 33
20 + 3 + 3 + 16 = 42
20 + 3 + 3 - 9 = 17
20 + 3 + 7 + 16 = 46
20 + 3 + 7 - 9 = 21
20 + 3 + 16 - 9 = 30
20 - 2 + 3 + 7 = 28
20 - 2 + 3 + 16 = 37
20 - 2 + 3 - 9 = 12
20 - 2 + 7 + 16 = 41
20 - 2 + 7 - 9 = 16
20 - 2 + 16 - 9 = 25
20 + 3 + 7 + 16 = 46
20 + 3 + 7 - 9 = 21
20 + 3 + 16 - 9 = 30
20 + 7 + 16 - 9 = 34
3 - 2 + 3 + 7 = 11
3 - 2 + 3 + 16 = 20
3 - 2 + 3 - 9 = -5
3 - 2 + 7 + 16 = 24
3 - 2 + 7 - 9 = -1
3 - 2 + 16 - 9 = 8
3 + 3 + 7 + 16 = 29
3 + 3 + 7 - 9 = 4
3 + 3 + 16 - 9 = 13
3 + 7 + 16 - 9 = 17
- 2 + 3 + 7 + 16 = 24
- 2 + 3 + 7 - 9 = -1
- 2 + 3 + 16 - 9 = 8
- 2 + 7 + 16 - 9 = 12
3 + 7 + 16 - 9 = 17
Update:
At the request of the OP, stopped when a solution is found.
8 + 20 + 3 - 2 = 29
8 + 20 + 3 + 3 = 34
8 + 20 + 3 + 7 = 38
8 + 20 + 3 + 16 = 47
8 + 20 + 3 - 9 = 22
8 + 20 - 2 + 3 = 29
8 + 20 - 2 + 7 = 33
8 + 20 - 2 + 16 = 42
8 + 20 - 2 - 9 = 17
8 + 20 + 3 + 7 = 38
8 + 20 + 3 + 16 = 47
8 + 20 + 3 - 9 = 22
8 + 20 + 7 + 16 = 51
8 + 20 + 7 - 9 = 26
8 + 20 + 16 - 9 = 35
8 + 3 - 2 + 3 = 12
8 + 3 - 2 + 7 = 16
8 + 3 - 2 + 16 = 25
8 + 3 - 2 - 9 = 0 <==
Related
This question was asked as a puzzle in one Book of Puzzles by RS AGGARWAL, which stated the problem as to build an order N matrix where each i'th row and i'th column combined have all the elements from 1 to 2N-1.
For instance, for N=2
[3,2]
[1,3]
I want to know when is an answer possible for it for which values of N it is possible to make a matrix and how to make it? and write code for it
this has simple solution for square matrices where n is power of 2 so n=1,2,4,8,16,... do not ask me why there surely is some math proof for it ...
The algorithm to create such matrix is easy:
clear matrix (with 0)
loop i through all values i=1,2,3...2n-1
for each i find all locations where i matrix is not yet filled (0) and there is not i present in row and column
fill the position with i and repeat until no such location found.
In C++ something like this:
//---------------------------------------------------------------------------
const int n=8;
int m[n][n];
//---------------------------------------------------------------------------
// compute histogram u[n+n] of values per ith row,col of m[n][n]
void hist_rst(int *u ) { for (int j=0;j<n+n;j++) u[j]=0; }
void hist_row(int *u,int m[n][n],int i) { for (int j=0;j<n;j++) u[m[j][i]]=1; }
void hist_col(int *u,int m[n][n],int i) { for (int j=0;j<n;j++) u[m[i][j]]=1; }
//---------------------------------------------------------------------------
void matrix_init(int m[n][n])
{
int i,x,y,h[n][n+n];
// clear matrix (unused cells)
for (x=0;x<n;x++)
for (y=0;y<n;y++)
m[x][y]=0;
// clear histograms
for (i=0;i<n;i++) hist_rst(h[i]);
// try to fill values 1..2n-1
for (i=1;i<n+n;i++)
{
// find free position
for (x=0;x<n;x++) if (!h[x][i])
for (y=0;y<n;y++) if (!h[y][i])
if (!m[x][y])
{
// set cell
m[x][y]=i;
h[x][i]=1;
h[y][i]=1;
break;
}
}
}
//---------------------------------------------------------------------------
here few outputs:
1
1 3
2 1
1 5 6 7
2 1 7 6
3 4 1 5
4 3 2 1
1 9 10 11 12 13 14 15
2 1 11 10 13 12 15 14
3 4 1 9 14 15 12 13
4 3 2 1 15 14 13 12
5 6 7 8 1 9 10 11
6 5 8 7 2 1 11 10
7 8 5 6 3 4 1 9
8 7 6 5 4 3 2 1
for non power of 2 matrices you could use backtracking but take in mind even 4x4 matrix will have many iterations to check ... so some heuristics would need to be in place to make it possible in finite time... as brute force is (n+n)^(n*n) so for n=4 there are 281474976710656 combinations to check ...
[edit1] genere&test solution for even n
//---------------------------------------------------------------------------
const int n=6;
int m[n][n];
//---------------------------------------------------------------------------
// compute histogram u[n+n] of values per ith row,col of m[n][n]
void hist_rst(int *u ) { for (int j=0;j<n+n;j++) u[j]=0; }
void hist_row(int *u,int m[n][n],int i) { for (int j=0;j<n;j++) u[m[j][i]]=1; }
void hist_col(int *u,int m[n][n],int i) { for (int j=0;j<n;j++) u[m[i][j]]=1; }
//---------------------------------------------------------------------------
void matrix_init2(int m[n][n]) // brute force
{
int x,y,a,ax[(n*n)>>1],ay[(n*n)>>1],an,u[n+n];
// clear matrix (unused cells)
for (x=0;x<n;x++)
for (y=0;y<n;y++)
m[x][y]=0;
// main diagonal 1,1,1,1...
for (x=0;x<n;x++) m[x][x]=1;
// 1st row 1,2,3...n
for (x=1;x<n;x++) m[x][0]=x+1;
// cells for brute force
for (an=0,x=0;x<n;x++)
for (y=0;y<x;y++)
if (!m[x][y])
{
ax[an]=x;
ay[an]=y;
an++;
m[x][y]=2;
}
// brute force attack values 2,3,4,5,...,n-1
for (;;)
{
// increment solution
for (a=0;a<an;a++)
{
x=ax[a];
y=ay[a];
m[x][y]++;
if (m[x][y]<=n) break;
m[x][y]=2;
}
if (a>=an) break; // no solution
// test
for (x=0;x<n;x++)
{
hist_rst(u);
hist_col(u,m,x);
hist_row(u,m,x);
for (y=1;y<=n;y++) if (!u[y]) { y=0; x=n; break; }
}
if (y) break; // solution found
}
// mirror other triangle
for (x=0;x<n;x++)
for (y=0;y<x;y++)
m[y][x]=m[x][y]+n-1;
}
//---------------------------------------------------------------------------
however its slow so do not try to go with n>6 without more optimizations/better heuristics... for now it is using triangle+mirror and diagonal + first row hard-coded heuristics.
maybe somehow exploit the fact that each iterated value will be placed n/2 times could speed this up more but too lazy to implement it ...
Here output for n=6:
[ 52.609 ms]
1 2 3 4 5 6
7 1 6 5 3 4
8 11 1 2 4 5
9 10 7 1 6 3
10 8 9 11 1 2
11 9 10 8 7 1
iterating through 5^10 cases ...
As requested by Spektre, here is the 6x6 matrix.
I an interesting property that may be used as heuristic. We need only to solve a triangular matrix because the other half can be easily deduced. We fill the upper (or lower) half of the matrix by values from 1 to n only. We can then complete the matrix by using the property that a[j][i] = 2n + 1 - a[i][j].
Another property I found is that there is a trivial way to place 1, 2 and N in the matrix. The values 1 are all on the diagonal, the values 2 and N are next to the diagonal at a step 2.
Finally, another thing I found is that matrix with odd N have no solutions. It is because the value in a[i][j] belongs to row and column i and row and column j. We thus need an even number of row and columns to store all values.
Here is the 6x6 matrix I found manually.
1 2 3 4 5 6
11 1 6 5 3 4
10 7 1 2 4 5
9 8 11 1 6 3
8 10 9 7 1 2
7 9 8 10 11 1
As we can see 2 + 11 = 6 + 7 = 3 + 10 = 13 = 2*6+1.
Here is a 4x4 matrix
1 2 3 4
7 1 4 3
6 5 1 2
5 6 7 1
Here again 2 + 7 = 4 + 5 = 3 + 6 = 9 = 2*4+1
It is possible to have other permutations of values >N, but with the 2N+1 property we can trivially deduce one triangular matrix from the other.
EDIT
Here is a solution for power two sized matrix. The matrix of size 2048x2048 is generated in 57ms (without printing).
#include <stdio.h>
int **newMatrix(int n) {
int **m = calloc(n, sizeof(int*));
m[0] = calloc(n*n, sizeof(int));
for (int i = 1; i < n; i++)
m[i] = m[0]+i*n;
return m;
}
void printMatrix(int **m, int n) {
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++)
printf("%3d ", m[i][j]);
printf("\n");
}
}
void fillPowerTwoMatrix(int **m, int n) {
// return if n is not power two
if (n < 0 || n&(n-1) != 0)
return;
for (int i = 0; i < n; i++)
m[0][i] = i+1;
for (int w = 1; w < n; w *= 2)
for (int k = 0; k < n; k += 2*w)
for (int i = 0; i < w; i++)
for (int j = k; j < k+w; j++) {
m[i+w][j] = m[i][j+w];
m[i+w][j+w] = m[i][j];
}
int k = 2*n+1;
for (int i = 1; i < n; i++)
for (int j = 0; j < i; j++)
m[i][j] = k - m[j][i];
}
int main() {
int n = 16;
int **m = newMatrix(n);
fillPowerTwoMatrix(m, n);
printMatrix(m, n);
return 0;
}
Here is the matrix 16x16. As can be seen there is a symmetry that is exploited to efficiently generate the matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
31 1 4 3 6 5 8 7 10 9 12 11 14 13 16 15
30 29 1 2 7 8 5 6 11 12 9 10 15 16 13 14
29 30 31 1 8 7 6 5 12 11 10 9 16 15 14 13
28 27 26 25 1 2 3 4 13 14 15 16 9 10 11 12
27 28 25 26 31 1 4 3 14 13 16 15 10 9 12 11
26 25 28 27 30 29 1 2 15 16 13 14 11 12 9 10
25 26 27 28 29 30 31 1 16 15 14 13 12 11 10 9
24 23 22 21 20 19 18 17 1 2 3 4 5 6 7 8
23 24 21 22 19 20 17 18 31 1 4 3 6 5 8 7
22 21 24 23 18 17 20 19 30 29 1 2 7 8 5 6
21 22 23 24 17 18 19 20 29 30 31 1 8 7 6 5
20 19 18 17 24 23 22 21 28 27 26 25 1 2 3 4
19 20 17 18 23 24 21 22 27 28 25 26 31 1 4 3
18 17 20 19 22 21 24 23 26 25 28 27 30 29 1 2
17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1
I'm wondering if someone can help me try to figure this out.
I want f(str) to take a string str of digits and return the sum of all substrings as numbers, and I want to write f as a function of itself so that I can try to solve this with memoization.
It's not jumping out at me as I stare at
Solve("1") = 1
Solve("2") = 2
Solve("12") = 12 + 1 + 2
Solve("29") = 29 + 2 + 9
Solve("129") = 129 + 12 + 29 + 1 + 2 + 9
Solve("293") = 293 + 29 + 93 + 2 + 9 + 3
Solve("1293") = 1293 + 129 + 293 + 12 + 29 + 93 + 1 + 2 + 9 + 3
Solve("2395") = 2395 + 239 + 395 + 23 + 39 + 95 + 2 + 3 + 9 + 5
Solve("12395") = 12395 + 1239 + 2395 + 123 + 239 + 395 + 12 + 23 + 39 + 95 + 1 + 2 + 3 + 9 + 5
You have to break f down into two functions.
Let N[i] be the ith digit of the input. Let T[i] be the sum of substrings of the first i-1 characters of the input. Let B[i] be the sum of suffixes of the first i characters of the input.
So if the input is "12395", then B[3] = 9+39+239+1239, and T[3] = 123+12+23+1+2+3.
The recurrence relations are:
T[0] = B[0] = 0
T[i+1] = T[i] + B[i]
B[i+1] = B[i]*10 + (i+1)*N[i]
The last line needs some explanation: the suffixes of the first i+2 characters are the suffixes of the first i+1 characters with the N[i] appended on the end, as well as the single-character string N[i]. The sum of these is (B[i]*10+N[i]*i) + N[i] which is the same as B[i]*10+N[i]*(i+1).
Also f(N) = T[len(N)] + B[len(N)].
This gives a short, linear-time, iterative solution, which you could consider to be a dynamic program:
def solve(n):
rt, rb = 0, 0
for i in xrange(len(n)):
rt, rb = rt+rb, rb*10+(i+1)*int(n[i])
return rt+rb
print solve("12395")
One way to look at this problem is to consider the contribution of each digit to the final sum.
For example, consider the digit Di at position i (from the end) in the number xn-1…xi+1Diyi-1…y0. (I used x, D, and y just to be able to talk about the digit positions.) If we look at all the substrings which contain D and sort them by the position of D from the end of the number, we'll see the following:
D
xD
xxD
…
xx…xD
Dy
xDy
xxDy
…
xx…xDy
Dyy
xDyy
xxDyy
…
xx…xDyy
and so on.
In other words, D appears in every position from 0 to i once for each prefix length from 0 to n-i-1 (inclusive), or a total of n-i times in each digit position. That means that its total contribution to the sum is D*(n-i) times the sum of the powers of 10 from 100 to 10i. (As it happens, that sum is exactly (10i+1−1)⁄9.)
That leads to a slightly simpler version of the iteration proposed by Paul Hankin:
def solve(n):
ones = 0
accum = 0
for m in range(len(n),0,-1):
ones = 10 * ones + 1
accum += m * ones * int(n[m-1])
return accum
By rearranging the sums in a different way, you can come up with this simple recursion, if you really really want a recursive solution:
# Find the sum of the digits in a number represented as a string
digitSum = lambda n: sum(map(int, n))
# Recursive solution by summing suffixes:
solve2 = lambda n: solve2(n[1:]) + (10 * int(n) - digitSum(n))/9 if n else 0
In case it's not obvious, 10*n-digitSum(n) is always divisible by 9, because:
10*n == n + 9*n == (mod 9) n mod 9 + 0
digitSum(n) mod 9 == n mod 9. (Because 10k == 1 mod n for any k.)
Therefore (10*n - digitSum(n)) mod 9 == (n - n) mod 9 == 0.
Looking at this pattern:
Solve("1") = f("1") = 1
Solve("12") = f("12") = 1 + 2 + 12 = f("1") + 2 + 12
Solve("123") = f("123") = 1 + 2 + 12 + 3 + 23 + 123 = f("12") + 3 + 23 + 123
Solve("1239") = f("1239") = 1 + 2 + 12 + 3 + 23 + 123 + 9 + 39 + 239 + 1239 = f("123") + 9 + 39 + 239 + 1239
Solve("12395") = f("12395") = 1 + 2 + 12 + 3 + 23 + 123 + 9 + 39 + 239 + 1239 + 5 + 95 + 395 + 2395 + 12395 = f("1239") + 5 + 95 + 395 + 2395 + 12395
To get the new terms, with n being the length of str, you are including the substrings made up of the 0-based index ranges of characters in str: (n-1,n-1), (n-2,n-1), (n-3,n-1), ... (n-n, n-1).
You can write a function to get the sum of the integers formed from the substring index ranges. Calling that function g(str), you can write the function recursively as f(str) = f(str.substring(0, str.length - 1)) + g(str) when str.length > 1, and the base case with str.length == 1 would just return the integer value of str. (The parameters of substring are the start index of a character in str and the length of the resulting substring.)
For the example Solve("12395"), the recursive equation f(str) = f(str.substring(0, str.length - 1)) + g(str) yields:
f("12395") =
f("1239") + g("12395") =
(f("123") + g("1239")) + g("12395") =
((f("12") + g("123")) + g("1239")) + g("12395") =
(((f("1") + g("12")) + g("123")) + g("1239")) + g("12395") =
1 + (2 + 12) + (3 + 23 + 123) + (9 + 39 + 239 + 1239) + (5 + 95 + 395 + 2395 + 12395)
Consider we have N points on a circle. To each point an index is assigned i = (1,2,...,N). Now, for a randomly selected point, I want to have a vector including the indices of 5 points, [two left neighbors, the point itself, two right neighbors].
See the figure below.
Some sxamples are as follows:
N = 18;
selectedPointIdx = 4;
sequence = [2 3 4 5 6];
selectedPointIdx = 1
sequence = [17 18 1 2 3]
selectedPointIdx = 17
sequence = [15 16 17 18 1];
The conventional way to code this is considering the exceptions as if-else statements, as I did:
if ii == 1
lseq = [N-1 N ii ii+1 ii+2];
elseif ii == 2
lseq = [N ii-1 ii ii+1 ii+2];
elseif ii == N-1
lseq=[ii-2 ii-1 ii N 1];
elseif ii == N
lseq=[ii-2 ii-1 ii 1 2];
else
lseq=[ii-2 ii-1 ii ii+1 ii+2];
end
where ii is selectedPointIdx.
It is not efficient if I consider for instance 7 points instead of 5. What is a more efficient way?
How about this -
off = -2:2
out = mod((off + selectedPointIdx) + 17,18) + 1
For a window size of 7, edit off to -3:3.
It uses the strategy of subtracting 1 + modding + adding back 1 as also discussed here.
Sample run -
>> off = -2:2;
for selectedPointIdx = 1:18
disp(['For selectedPointIdx =',num2str(selectedPointIdx),' :'])
disp(mod((off + selectedPointIdx) + 17,18) + 1)
end
For selectedPointIdx =1 :
17 18 1 2 3
For selectedPointIdx =2 :
18 1 2 3 4
For selectedPointIdx =3 :
1 2 3 4 5
For selectedPointIdx =4 :
2 3 4 5 6
For selectedPointIdx =5 :
3 4 5 6 7
For selectedPointIdx =6 :
4 5 6 7 8
....
For selectedPointIdx =11 :
9 10 11 12 13
For selectedPointIdx =12 :
10 11 12 13 14
For selectedPointIdx =13 :
11 12 13 14 15
For selectedPointIdx =14 :
12 13 14 15 16
For selectedPointIdx =15 :
13 14 15 16 17
For selectedPointIdx =16 :
14 15 16 17 18
For selectedPointIdx =17 :
15 16 17 18 1
For selectedPointIdx =18 :
16 17 18 1 2
You can use modular arithmetic instead: Let p be the point among N points numbered 1 to N. Say you want m neighbors on each side, you can get them as follows:
(p - m - 1) mod N + 1
...
(p - 4) mod N + 1
(p - 3) mod N + 1
(p - 2) mod N + 1
p
(p + 1) mod N + 1
(p + 2) mod N + 1
(p + 3) mod N + 1
...
(p + m - 1) mod N + 1
Code:
N = 18;
p = 2;
m = 3;
for i = p - m : p + m
nb = mod((i - 1) , N) + 1;
disp(nb);
end
Run code here
I would like you to note that you might not necessarily improve performance by avoiding a if statement. A benchmark might be necessary to figure this out. However, this will only be significant if you are treating tens of thousands of numbers.
I was searching around the internet trying to find the algorithm of the following pyramid:
1
2 3 2
3 4 5 4 3
4 5 6 7 6 5 4
5 6 7 8 9 8 7 6 5
6 7 8 9 10 11 10 9 8 7 6
7 8 9 10 11 12 13 12 11 10 9 8 7
8 9 10 11 12 13 14 15 14 13 12 11 10 9 8
9 10 11 12 13 14 15 16 17 16 15 14 13 12 11 10 9
10 11 12 13 14 15 16 17 18 19 18 17 16 15 14 13 12 11 10
I wasn't able to find the algorithm, my question is: Does anyone know the algorithm and/or name for this type of pyramid?
Any help is greatly appreciated. I'm sorry if anything in the post is wrong in some way, new posting here.
Here's one solution .... but you should not be lazy, this isn't so hard :)
It is written in Java ....
What you see in the System.out.print() is "Ternary operator". You need to check if it is two digit number, to reduce the number of empty spaces.
public static void Pyramid(int rows) {
int r = 1; // r is current row
int emptySpaces = rows;
while(r <= rows) {
//print the empty spaces (3 empty spaces in one iteration)
for(int i = 1; i < emptySpaces; i++) {
System.out.print(" ");
}
//print the numbers to the middle including the middle number
for(int i = 0; i < r; i++) {
System.out.print((r+i)/10 == 0 ? (r+i + " ") : (r+i + " "));
}
//print the numbers from the middle to the end
for(int i = r-2; i >= 0; i--) {
System.out.print((r+i)/10 == 0 ? (r+i + " ") : (r+i + " "));
}
//print new line, reduce empty spaces
System.out.println("");
emptySpaces--;
r++;
}
}
What is a mathematical way of of saying 1 - 1 = 12 for a month calculation? Adding is easy, 12 + 1 % 12 = 1, but subtraction introduces 0, stuffing things up.
My actual requirement is x = x + d, where x must always be between 1 and 12 before and after the summing, and d any unsigned integer.
Assuming x and y are both in the range 1-12:
((x - y + 11) % 12) + 1
To break this down:
// Range = [0, 22]
x - y + 11
// Range = [0, 11]
(x - y + 11) % 12
// Range = [1, 12]
((x - y + 11) % 12) + 1
I'd work internally with a 0 based month (0-11), summing one for external consumption only (output, another calling method expecting 1-12, etc.), that way you can wrap around backwards just as easily as wrapping around forward.
>>> for i in range(15):
... print '%d + 1 => %d' % (i, (i+1)%12)
...
0 + 1 => 1
1 + 1 => 2
2 + 1 => 3
3 + 1 => 4
4 + 1 => 5
5 + 1 => 6
6 + 1 => 7
7 + 1 => 8
8 + 1 => 9
9 + 1 => 10
10 + 1 => 11
11 + 1 => 0
12 + 1 => 1
13 + 1 => 2
14 + 1 => 3
>>> for i in range(15):
... print '%d - 1 => %d' % (i, (i-1)%12)
...
0 - 1 => 11
1 - 1 => 0
2 - 1 => 1
3 - 1 => 2
4 - 1 => 3
5 - 1 => 4
6 - 1 => 5
7 - 1 => 6
8 - 1 => 7
9 - 1 => 8
10 - 1 => 9
11 - 1 => 10
12 - 1 => 11
13 - 1 => 0
14 - 1 => 1
You have to be careful with addition, too, since (11 + 1) % 12 = 0. Try this:
x % 12 + 1
This comes from using a normalisation function:
norm(x) = ((x - 1) % 12) + 1
Substituting,
norm(x + 1) = (((x + 1) - 1) % 12 + 1
norm(x + 1) = (x) % 12 + 1
The % (modulus) operator produces an answer in the range 0..(N-1) for x % N. Given that your inputs are in the range 1..N (for N = 12), the general adding code for adding a positive number y months to current month x should be:
(x + y - 1) % 12 + 1
When y is 1, this reduces to
x % 12 + 1
Subtracting is basically the same. However, there are complications with the answers produced by different implementations of the modulus operator when either (or both) of the operands is negative. If the number to be subtracted is known to be in in the range 1..N, then you can use the fact that subtracting y modulo N is the same as adding (N - y) modulo N. If y is unconstrained (but positive), then use:
(x + (12 - (y % 12) - 1) % 12 + 1
This double-modulo operation is a common part of the solution to problems like this when the range of the values is not under control.