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  1. from collections import deque
  2. import numpy as np
  3.  
  4. asp = np.array([[ 2, 1, 8, 2],
  5.                 [ 5, 4, 6, 4],
  6.                 [ 3, 3, 3, 3],
  7.                 [ 2, 1, 8, 2]])  #aspect
  8. slp = np.array([[11,11,12,11],
  9.                 [12,11,12,10],
  10.                 [ 9, 9, 9,10],
  11.                 [11,10,11,11]])  #slope
  12. elv = np.array([[16,15,15,16],
  13.                 [17,15,15,15],
  14.                 [15,15,14,14],
  15.                 [16,15,16,16]]) #elevation
  16.  
  17. criteria = np.stack((asp, slp, elv))
  18.  
  19. def floodfill(n, start):
  20.     def check(r, c):
  21.         return result[r, c] == 0 and np.array_equal(crit, criteria[:, r, c])
  22.  
  23.     stack = deque([start])
  24.     crit = criteria [(slice(None), *start)]
  25.     while stack:
  26.         r, c = stack.popleft()
  27.         if result[r, c]: continue
  28.         result[r, c] = n
  29.         if r > 0 and check(r - 1, c):
  30.             stack.append((r - 1, c))
  31.         if r < result.shape[0] - 1 and check(r + 1, c):
  32.             stack.append((r + 1, c))
  33.         if c > 0 and check(r, c - 1):
  34.             stack.append((r, c - 1))
  35.         if c < result.shape[1] - 1 and check(r, c + 1):
  36.             stack.append((r, c + 1))
  37.  
  38.  
  39. result = np.zeros_like(asp)
  40. count = 1
  41. it = np.nditer(result, flags=['multi_index'])
  42. for x in it:
  43.     if x == 0:
  44.         floodfill(count, it.multi_index)
  45.         count += 1
  46.  
  47. print(result)
Success #stdin #stdout 0.07s 92224KB
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[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9  9 10 11]
 [12 13 14 15]]
https://ideone.com/9JuHjt
language:
Python 3 (python  3.12)
created:
6 years ago
visibility:
public

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