I translated a grayscale picture into a matrix that contains the intensity values of each pixel as integers. Now I’m looking for a way to sort the matrix by its pixel intensity values. Take the following matrix for example:

The output should be:

I couldn’t get the desired result using `numpy.sort`

, does anyone have an idea how to do this?

**EDIT:** Here’s the code:

```
import numpy as np
import matplotlib.pyplot as plt
# Pillow library, to manipulate images
from PIL import Image
# reading image with PIL module
original = Image.open('original_reduced.png')
# converting it to a numpy array. numpy arrays are easier to manipulate
im_original = np.array(original)
#plt.imshow(im_original, cmap='gray', vmin=0, vmax=255)
# size of full image
im_original.shape
## size and cropping coordinates
s = 170
x, y = 85, 85
# crops image of his face
im = im_original[y:y+s, x:x+s]
## im_b should be "im" sorted
im_b = ???
#print(im)
#print(im_b)
plt.imshow(im_b, cmap='gray', vmin=0, vmax=255)
plt.show()
```

### >Solution :

You can sort the flattened array and `reshape`

to original shape in Fortran-like order:

```
np.sort(a.ravel()).reshape(a.shape, order='F')
```

input:

```
a = np.array([[4,2,1,3],
[6,5,7,8],
[11,10,9,12]
])
```

output:

```
array([[ 1, 4, 7, 10],
[ 2, 5, 8, 11],
[ 3, 6, 9, 12]])
```