Follow

Keep Up to Date with the Most Important News

By pressing the Subscribe button, you confirm that you have read and are agreeing to our Privacy Policy and Terms of Use
Contact

Comparing with adjacent values in Python

I want to compare the minimum value of each row with the nearby elements. For example, min of first row occurs at Pe[0,1]. I want to compare this value with Pe[0,0], Pe[0,2] and Pe[1,1] and find the minimum amongst these three. Similarly for other rows. How to code it?

import numpy as np
Pe=np.array([[0.97300493, 0.4630001 , 0.66754101],
       [0.09043881, 0.03976944, 0.64823791],
       [0.9530546 , 0.40305156, 0.20944696]])

Pe_min=Pe.argmin(axis=1)

>Solution :

MEDevel.com: Open-source for Healthcare and Education

Collecting and validating open-source software for healthcare, education, enterprise, development, medical imaging, medical records, and digital pathology.

Visit Medevel

You can do this by looping over your rows, but it’s a bit tedious, I’m sure there’s a smarter way:

import numpy as np

a = np.array([[0.97300493, 0.4630001 , 0.66754101],
             [0.09043881, 0.03976944, 0.64823791],
             [0.9530546 , 0.40305156, 0.20944696]])
b = np.zeros((a.shape[0], 2))

for row_n, row in enumerate(a):
   # Get row min
   b[row_n][0] = np.min(row)
   
   # Get surroundings min
   i = np.argmin(row)
   near = []
   if row_n > 0:
      near.append(a[row_n-1][i])
   if row_n+1 < b.shape[0]:
      near.append(a[row_n+1][i])
   if i > 0:
      near.append(a[row_n][i-1])
   if i+1 < b.shape[1]:
      near.append(a[row_n][i+1])
   b[row_n][1] = min(near)

print(b)
# array([[0.4630001 , 0.03976944],
#       [0.03976944, 0.09043881],
#       [0.20944696, 0.40305156]])
Add a comment

Leave a Reply

Keep Up to Date with the Most Important News

By pressing the Subscribe button, you confirm that you have read and are agreeing to our Privacy Policy and Terms of Use

Discover more from Dev solutions

Subscribe now to keep reading and get access to the full archive.

Continue reading