user4555363 - 7 months ago 79

Python Question

`import numpy as np`

def calc_size(matrix, index):

return np.nonzero(matrix[index,:])[1].size

def swap_rows(matrix, frm, to):

matrix[[frm, to],:] = matrix[[to, frm],:]

Numpy - Python 2.7

How can I achieve that matrix's rows are sorted after the size of the nonzero entries? I already wrote these two methods for doing the work but I need to give it to a sorting engine? The fullest rows should be at the beginning!

Answer

If you have an array `arr`

:

```
array([[0, 0, 0, 0, 0],
[1, 0, 1, 1, 1],
[0, 1, 0, 1, 1],
[1, 1, 1, 1, 1]])
```

You could sort the array's rows according to the number of zero entries by writing:

```
>>> arr[(arr == 0).sum(axis=1).argsort()]
array([[1, 1, 1, 1, 1],
[1, 0, 1, 1, 1],
[0, 1, 0, 1, 1],
[0, 0, 0, 0, 0]])
```

This first counts the number of zero entries in each row with `(arr == 0).sum(axis=1)`

: this produces the array `[5, 1, 2, 0]`

.

Next, `argsort`

sorts the indices of this array by their corresponding value, giving `[3, 1, 2, 0]`

.

Lastly, this argsorted array is used to rearrange the rows of `arr`

.

P.S. If you have a matrix `m`

(and not an array), you may need to ravel before using `argsort`

:

```
m[(m == 0).sum(axis=1).ravel().argsort()]
```

Source (Stackoverflow)