CODEWITHSUNDEEP
pythoniteration
user18091161
user18091161

Reputation:

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)

Upvotes: 0

Views: 81

Answers (2)

Alain T.
Alain T.

Reputation: 42143

You could get a vectorized solution in 4 steps by assigning the minimums with shifted sub ranges on the previous and next rows/columns:

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]])

r = a.copy()
r[:,:-1] = np.minimum(r[:,:-1],a[:,1:]) # min with next columns
r[:,1:]  = np.minimum(r[:,1:],a[:,:-1]) # min with previous columns
r[:-1,:] = np.minimum(r[:-1,:],a[1:,:]) # min with next rows
r[1:,:]  = np.minimum(r[1:,:],a[:-1,:]) # min with previous rows

print(r)
[[0.09043881 0.03976944 0.4630001 ]
 [0.03976944 0.03976944 0.03976944]
 [0.09043881 0.03976944 0.20944696]]

Upvotes: 1

Ari Cooper-Davis
Ari Cooper-Davis

Reputation: 3485

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]])

Upvotes: 0

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