Given a square matrix (i.e. an array of subarrays), find the sum of values from the first value of the first array, the second value of the second array, the third value of the third array, and so on...

## Examples

```
array = [[1, 2],
         [3, 4]]

diagonal sum: 1 + 4 = 5
```
                
```
array = [[5, 9, 1, 0],
         [8, 7, 2, 3],
         [1, 4, 1, 9],
         [2, 3, 8, 2]]

diagonal sum: 5 + 7 + 1 + 2 = 15
```

Difficulty: introductory

Starter code:

def diagonal_sum(array):
	

Solutions:
def diagonal_sum(array):
    return sum(row[i] for i, row in enumerate(array))

from numpy import trace as diagonal_sum

def diagonal_sum(array):
    
    return sum([array[a][a] for a in range(len(array))])

def diagonal_sum(array):
    return sum( row[idx] for idx, row in enumerate(array) )

def diagonal_sum(array):
    return sum([array[x][x] for x in range(0,len(array))])


def diagonal_sum(array):
     sum=0
     for x in range(len(array)):
          for y in range(len(array[x])):
               if x==y:
                  sum=sum+array[x][y]
     return(sum)

def diagonal_sum(array):
    return sum([row[i] for i, row in enumerate(array)])

def diagonal_sum(a):
    return sum(l[i] for i, l in enumerate(a))

def diagonal_sum(array):
    return sum(line[i] for i, line in enumerate(array))

def diagonal_sum(array):
    sum = 0
    for n in range(len(array)):
        sum += array[n][n]
    return sum