Sorting a matrix by value in Python

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]])
``````