I am fairly new to C++, and am struggling through a problem that seems to have a solid solution but I just can't seem to find it. I have a contiguous array of ints starting at zero:
int i[6] = { 0, 1, 2, 3, 4, 5 }; // this is actually from an iterator
I would like to partition the array into groups of three. The design is to have two methods, j and k, such that given an i they will return the other two elements from the same group of three. For example:
i j(i) k(i)
0 1 2
1 0 2
2 0 1
3 4 5
4 3 5
5 3 4
The solution seems to involve summing the i with its value mod three and either plus or minus one, but I can't quite seem to work out the logic.
This should work:
int d = i % 3;
int j = i - d + ( d == 0 );
int k = i - d + 2 - ( d == 2 );
or following statement for k could be more readable:
int k = i - d + ( d == 2 ? 1 : 2 );
This should do it:
int j(int i)
{
int div = i / 3;
if (i%3 != 0)
return 3*div;
else
return 3*div+1;
}
int k(int i)
{
int div = i / 3;
if (i%3 != 2)
return 3*div+2;
else
return 3*div+1;
}
Test.
If you want shorter functions:
int j(int i)
{
return i/3*3 + (i%3 ? 0 : 1);
}
int k(int i)
{
return i/3*3 + (i%3-2 ? 2 : 1);
}
Well, first, notice that
j(i) == j(3+i) == j(6+i) == j(9+i) == ...
k(i) == k(3+i) == k(6+i) == k(9+i) == ...
In other words, you only need to find a formula for
j(i), i = 0, 1, 2
k(i), i = 0, 1, 2
and then for the rest of the cases simply plug in i mod 3.
From there, you'll have trouble finding a simple formula because your "rotation" isn't standard. Instead of
i j(i) k(i)
0 1 2
1 2 0
2 0 1
for which the formula would have been
j(i) = (i + 1) % 3
k(i) = (i + 2) % 3
you have
i j(i) k(i)
0 1 2
1 0 1
2 0 2
for which the only formula I can think of at the moment is
j(i) = (i == 0 ? 1 : 0)
k(i) = (i == 1 ? 1 : 2)
If the values of your array (let's call it arr, not i in order to avoid confusion with the index i) do not coincide with their respective index, you have to perform a reverse lookup to figure out their index first. I propose using an std::map<int,size_t> or an std::unordered_map<int,size_t>.
That structure reflects the inverse of arr and you can extra the index for a particular value with its subscript operator or the at member function. From then, you can operate purely on the indices, and use modulo (%) to access the previous and the next element as suggested in the other answers.
Related
I represent a n*m matrix like chessboard.
1 0 2 0
0 3 0 4
5 0 6 0
0 7 0 8
I don't need to store the zeros in my 1d vector.
vector v = {1, 2, 3, 4.. etc}
I ask the user for a row and column number.
How can i return with i. row j. column element?
if (i+j) % 2 != 0
I return with 0, but i don't know what i need to do when
(i+j) % 2 == 0
Can you help me? (sorry for my bad English)
With regular matrices stored as 1D-vector, coordinate to index would be:
(i + j * width) (or i * height + j depending on convention).
with half case to 0, you just have to divide by 2:
if ((i + j) % 2 != 0) return 0;
else return data[(i + j * width) / 2];
I have two dimensional array of chars, where all numbers, excluding one * (as given in picture (two examples)
My task is to sum up all neighbour integers ( in example 1, neighbours of * are 4,2,5,8 and sum is 4+2+5+8=19)
But in example 2, * doesn't have top neighbour.
My initial code was like:
arr[i-1][j] + arr[i+1][j] + arr[i][j-1] + arr[i][j+1]
But then I understood that in case like a[0][-1] doesn't exist. So can you help me to to solve my problem
You need to explicitly check each one. The following should work:
bool inRange(int i, int j) {
const auto n = 4; // you need to set this somewhere, or pass it in
return (i >= 0) && (i < n) && (j >= 0) && (j < n);
}
auto sum = (inRange(i-1, j) ? arr[i-1][j] : 0)
+ (inRange(i+1, j) ? arr[i+1][j] : 0)
+ (inRange(i, j-1) ? arr[i][j-1] : 0)
+ (inRange(i, j+1) ? arr[i][j+1] : 0);
You can probably write this a little cleaner, but you need to check not only for the -1, but also for when you go over 3.
There can be multiple solutions to this problem, but if you want to avoid checking bound each time you can extend the matrix dimension by 1 than needed. That means if you have an array:
1 * 4 7
8 9 2 3
5 1 2 4
4 3 6 5
Implement it as:
0 0 0 0 0 0
0 1 * 4 7 0
0 8 9 2 3 0
0 5 1 2 4 0
0 4 3 6 5 0
0 0 0 0 0 0
Doing this won't even affect your sum at the end.
I would like to find a mapping f:X --> N, with multiple discrete natural variables X of varying dimension, where f produces a unique number between 0 to the multiplication of all dimensions. For example. Assume X = {a,b,c}, with dimensions |a| = 2, |b| = 3, |c| = 2. f should produce 0 to 12 (2*3*2).
a b c | f(X)
0 0 0 | 0
0 0 1 | 1
0 1 0 | 2
0 1 1 | 3
0 2 0 | 4
0 2 1 | 5
1 0 0 | 6
1 0 1 | 7
1 1 0 | 8
1 1 1 | 9
1 2 0 | 10
1 2 1 | 11
This is easy when all dimensions are equal. Assume binary for example:
f(a=1,b=0,c=1) = 1*2^2 + 0*2^1 + 1*2^0 = 5
Using this naively with varying dimensions we would get overlapping values:
f(a=0,b=1,c=1) = 0*2^2 + 1*3^1 + 1*2^2 = 4
f(a=1,b=0,c=0) = 1*2^2 + 0*3^1 + 0*2^2 = 4
A computationally fast function is preferred as I intend to use/implement it in C++. Any help is appreciated!
Ok, the most important part here is math and algorythmics. You have variable dimensions of size (from least order to most one) d0, d1, ... ,dn. A tuple (x0, x1, ... , xn) with xi < di will represent the following number: x0 + d0 * x1 + ... + d0 * d1 * ... * dn-1 * xn
In pseudo-code, I would write:
result = 0
loop for i=n to 0 step -1
result = result * d[i] + x[i]
To implement it in C++, my advice would be to create a class where the constructor would take the number of dimensions and the dimensions itself (or simply a vector<int> containing the dimensions), and a method that would accept an array or a vector of same size containing the values. Optionaly, you could control that no input value is greater than its dimension.
A possible C++ implementation could be:
class F {
vector<int> dims;
public:
F(vector<int> d) : dims(d) {}
int to_int(vector<int> x) {
if (x.size() != dims.size()) {
throw std::invalid_argument("Wrong size");
}
int result = 0;
for (int i = dims.size() - 1; i >= 0; i--) {
if (x[i] >= dims[i]) {
throw std::invalid_argument("Value >= dimension");
}
result = result * dims[i] + x[i];
}
return result;
}
};
Description:
Given matrix [x] [y], with x- rows and y- number of columns . Filled random numbers from 0 to 5 inclusive .
Description of finding a solution : the solution is considered to be a set of matrix elements that are adjacent to each other ( diagonal neighborhood is not taken into account ) and the sum of the number are 10. Each element of the matrix can be used 1 time for a decision . The solution may have any number of digits. The decision must end any number other than zero .
Example:
given
0 1 2 3 4 5
1 2 3 4 5 0
2 3 4 5 1 2
Solution 1 : (1 - 2 - 3 - 4)
0 **1** 2 3 4 5
1 **2** 3 4 5 0
2 **3** **4** 5 1 2
i tried to do smth like this, but it is wrong, i dont know when i must stop,
Solution it is a class which contains mair of indexes, pls help me.
void xxx(int colCount, int rowCount, int currentRow, int currentCol, int** matrix, int sum, Solution *solution, int solCount) {
sum += matrix[currentRow][currentCol];
matrix[currentRow][currentCol] = -1;
if(sum > 10){
sum - = matrix[currentRow][currentCol];
return;
} else if(sum == 10){
solution[solCount].additem(currentRow, currentCol);
return xxx(5,5,currentRow - 1, currentCol, matrix, sum, solution, solCount+1);
} else {
//UP
if( currentRow > 0 && matrix [currentRow - 1][currentCol] != -1){
xxx(5,5,currentRow - 1, currentCol, matrix, sum, solution,solCount);
}
//LEFT
if(currentCol > 0 && matrix [currentRow][currentCol-1] != -1){
xxx(5,5,currentRow, currentCol - 1, matrix, sum, solution,solCount);
}
//DOWN
if(currentRow + 1 < colCount && matrix[currentRow + 1][currentCol] != -1){
xxx(5,5,currentRow + 1, currentCol, matrix, sum, solution,solCount);
}
//RIGHT
if(currentCol + 1 < rowCount && matrix[currentRow][currentCol + 1] != -1){
xxx(5,5,currentRow, currentCol + 1, matrix, sum, solution,solCount);
}
}
}
int sum_down(int x)
{
if (x >= 0)
{
x = x - 1;
int y = x + sum_down(x);
return y + sum_down(x);
}
else
{
return 1;
}
}
What is this smallest integer value of the parameter x, so that the returned value is greater than 1.000.000 ?
Right now I am just doing it by trial and error and since this question is asked via a paper format. I don't think I will have enough time to do trial and error. Question is, how do you guys visualise this quickly such that it can be solved easily. Thanks guys and I am new to programming so thanks in advance!
The recursion logic:
x = x - 1;
int y = x + sum_down(x);
return y + sum_down(x);
can be simplified to:
x = x - 1;
int y = x + sum_down(x) + sum_down(x);
return y;
which can be simplified to:
int y = (x-1) + sum_down(x-1) + sum_down(x-1);
return y;
which can be simplified to:
return (x-1) + 2*sum_down(x-1);
Put in mathematical form,
f(N) = (N-1) + 2*f(N-1)
with the recursion terminating when N is -1. f(-1) = 1.
Hence,
f(0) = -1 + 2*1 = 1
f(1) = 0 + 2*1 = 2
f(2) = 1 + 2*2 = 5
...
f(18) = 17 + 2*f(17) = 524269
f(19) = 18 + 2*524269 = 1048556
Your program can be written this way (sorry about c#):
public static void Main()
{
int i = 0;
int j = 0;
do
{
i++;
j = sum_down(i);
Console.Out.WriteLine("j:" + j);
} while (j < 1000000);
Console.Out.WriteLine("i:" + i);
}
static int sum_down(int x)
{
if (x >= 0)
{
return x - 1 + 2 * sum_down(x - 1);
}
else
{
return 1;
}
}
So at first iteration you'll get 2, then 5, then 12... So you can neglect the x-1 part since it'll stay little compared to the multiplication.
So we have:
i = 1 => sum_down ~= 4 (real is 2)
i = 2 => sum_down ~= 8 (real is 5)
i = 3 => sum_down ~= 16 (real is 12)
i = 4 => sum_down ~= 32 (real is 27)
i = 5 => sum_down ~= 64 (real is 58)
So we can say that sum_down(x) ~= 2^x+1. Then it's just basic math with 2^x+1 < 1 000 000 which is 19.
A bit late, but it's not that hard to get an exact non-recursive formula.
Write it up mathematically, as explained in other answers already:
f(-1) = 1
f(x) = 2*f(x-1) + x-1
This is the same as
f(-1) = 1
f(x+1) = 2*f(x) + x
(just switched from x and x-1 to x+1 and x, difference 1 in both cases)
The first few x and f(x) are:
x: -1 0 1 2 3 4
f(x): 1 1 2 5 12 27
And while there are many arbitrary complicated ways to transform this into a non-recursive formula, with easy ones it often helps to write up what the difference is between each two elements:
x: -1 0 1 2 3 4
f(x): 1 1 2 5 12 27
0 1 3 7 15
So, for some x
f(x+1) - f(x) = 2^(x+1) - 1
f(x+2) - f(x) = (f(x+2) - f(x+1)) + (f(x+1) - f(x)) = 2^(x+2) + 2^(x+1) - 2
f(x+n) - f(x) = sum[0<=i<n](2^(x+1+i)) - n
With eg. a x=0 inserted, to make f(x+n) to f(n):
f(x+n) - f(x) = sum[0<=i<n](2^(x+1+i)) - n
f(0+n) - f(0) = sum[0<=i<n](2^(0+1+i)) - n
f(n) - 1 = sum[0<=i<n](2^(i+1)) - n
f(n) = sum[0<=i<n](2^(i+1)) - n + 1
f(n) = sum[0<i<=n](2^i) - n + 1
f(n) = (2^(n+1) - 2) - n + 1
f(n) = 2^(n+1) - n - 1
No recursion anymore.
How about this :
int x = 0;
while (sum_down(x) <= 1000000)
{
x++;
}
The loop increments x until the result of sum_down(x) is superior to 1.000.000.
Edit : The result would be 19.
While trying to understand and simplify the recursion logic behind the sum_down() function is enlightening and informative, this snippet tend to be logical and pragmatic in that it does not try and solve the problem in terms of context, but in terms of results.
Two lines of Python code to answer your question:
>>> from itertools import * # no code but needed for dropwhile() and count()
Define the recursive function (See R Sahu's answer)
>>> f = lambda x: 1 if x<0 else (x-1) + 2*f(x-1)
Then use the dropwhile() function to remove elements from the list [0, 1, 2, 3, ....] for which f(x)<=1000000, resulting in a list of integers for which f(x) > 1000000. Note: count() returns an infinite "list" of [0, 1, 2, ....]
The dropwhile() function returns a Python generator so we use next() to get the first value of the list:
>>> next(dropwhile(lambda x: f(x)<=1000000, count()))
19