In order to sum the elements above and below the diagonal, the array must be perfectly square. To guarantee the array is square we'll use a class template to implement an array of N arrays of length N. The following program demonstrates the minimal implementation required to sum the elements above and below the diagonal and will work for any array type for which operator+ is defined, which includes all the built-in numeric types such as int and double. operator<< has also been overloaded to assist in printing the array.
#include
#include
template
class square_array {
private:
std::array
public:
T sum_above (void) const;
T sum_below (void) const;
const std::array
std::array
};
template
T square_array
T sum = 0;
for (size_t row=0; row for (size_t col=row+1; col sum += data[row][col]; return sum; } template T square_array T sum = 0; for (size_t row=0; row for (size_t col=0; col sum += data[row][col]; return sum; } template std::ostream& operator<< (std::ostream& os, const square_array os << '{'; for (size_t row=0; row os << '{'; for (size_t col=0; col os << sa[row][col]; if (col } os << '}'; if (row } os << '}'; return os; } int main (void) { std::default_random_engine engine; std::uniform_int_distribution square_array // initialise elements with random values (range: 1 to 9) for (size_t row=0; row<5; ++row) for (size_t col=0; col<5; ++col) sa[row][col] = dist (engine); std::cout<<"Array = "< std::cout<<"Sum above: "< std::cout<<"Sum below: "< }
#include<iostream> #include<random> #include<time.h> int main() { std::default_random_engine generator ((unsigned)time(0)); std::uniform_int_distribution<int> distribution (1,9); std::cout << "Array:\n" << std::endl; int a[3][3]; for (size_t r=0; r!=3; ++r) { for (size_t c=0; c!=3; ++c) { a[r][c] = distribution (generator); std::cout << a[r][c] << '\t'; } std::cout << std::endl; } std::cout << std::endl; int diagonal=0, anti_diagonal=0; for (size_t i=0; i!=3; ++i) { diagonal += a[i][i]; anti_diagonal += a[2-i][i]; } std::cout << "Diagonal sum : " << diagonal << std::endl; std::cout << "Anti-diagonal sum : " << anti_diagonal << std::endl; }
both
Please rephrase your question. An array usually has a fixed size and I don't recall ever having to "go below its size". This implies that the missing elements are not within the range of the array.
The Java main method of a program is the place where the program execution begins. A main method would look like below public static void main(String[] args){ }
class firstprog { public static void main (String args[]) { System.out.pritnln("My first Program in Java "); } } Simple Java Programe Write the above program in Ms dos's edit or Notepad of Windows save it with "firstprog.java" run the commands given below in command prompt of Ms Dos to get the output Remamber Java is case sensative so mentain capital and small letter. 1. javac firstprog.java 2. java firstprog
A tridiagonal matrix is one in which the only non-zero elements are on the principal diagonal, and the two diagonals immediately next to it: one below and the other above.
See a complete list at the link below.
Silicon on its right , Boron above, and Gallium below it.
This affirmation is not correct; the half lives are different.
Below it on the list on the periodic table
No
make a table as I did below for the set {a,b,c} with 3 elements. A table with all n elements will represent all the possible relations on that set of n elements. We can use the table to find all types of relations, transitive, symmetric etc. | a | b | c | --+---+---+---+ a | * | | | b | | * | | c | | | * | The total number of relations is 2^(n^2) because for each a or b we can include or not include it so there are 2 possibilities and there are n^2 elements so 2^(n^2) total relations. A relation is reflexive if contains all pairs of the form {x,x) for any x in the set. So this is the diagonal of your box. THESE ARE FIXED! No, in reflexive relation we still can decide to include or not include any of the other elements. So we have n diagonal elements that are fixed and we subtract that from n^2 so we have 2^(n^2-n) If you do the same thing for symmetric relations you will get 2^(n(n+1)/2). We get this by picking all the squares on the diagonal and all the ones above it too.
above - sky as below - ground above - airplane as below - subway
cuba is above and the Caribbean sea is below
Briefly, the variance for a variable is a measure of the dispersion or spread of scores. Covariance indicates how two variables vary together. The variance-covariance matrix is a compact way to present data for your variables. The variance is presented on the diagonal (where the column and row intersect for the same variable), while the covariances reside above or below the diagonal.
As above so below? How about water? Not always so.
Program below?!