Vadim - 1 month ago 12

Python Question

No matter how the other elements are positioned, is important only the values along the diagonal.

For example I have matrix:

`matrix = [[1, 3, 2],`

[2, 5, -9],

[3, 4, 6]]

What I want to achieve is something the same as:

`[[-9, 3, 2],`

[6, 1, 5],

[3, 4, 2]]

I have tried:

`>>> np_matrix = np.array(matrix)`

>>> np_matrix.diagonal()

array([1, 5, 6])

>>> np.sort(np_matrix)

array([[ 1, 2, 3],

[-9, 2, 5],

[ 3, 4, 6]])

I think that I can get something from these methods, but I can not figure out how to make them work together. I appreciate all the help I can get.

Answer

I am not really sure what you want. But maybe something like

```
sorted = np.sort(matrix, axis=None) #sorts flattened matrix
```

Now you have reshape it, and then change the diagonal elements with the first row:

```
sorted.shape = matrix.shape
for i in xrange(1, matrix.shape[0]): # first element already in order
sorted[0, i], sorted[i, i] = sorted[i, i], sorted[0, i]
```

But honestly I would first question if that really is what you want. It doesn't seem really useful to me. Isn't it maybe enough to get an array with the smallest elements

`diag_lowest = np.sort(matrix, axis=None)[:matrix.shape[0]]`

and keep the matrix as it is.