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  1. [[-1.  1.  0.]
  2.  [ 0.  0.  0.]
  3.  [ 0. -1.  1.]
  4.  [ 0.  0.  0.]
  5.  [ 0. -1.  1.]
  6.  [ 0.  0.  0.]]
  7.    
  8. K([0,2],:)
  9.    
  10. myList = []    
  11. for i in range(len(K)): #generate pairs
  12.     for j in range(i+1,len(K)):  #travel down each other rows
  13.         if np.array_equal(K[i],K[j]) and np.any(K[i] != 0, axis=1) and np.any(K[j] != 0, axis=1):
  14.         myList.append(K[i])
  15.         print ('indices of similar-non-zeros rows aren',(i, j)),
  16.         elif not np.array_equal(K[i],K[j]) and np.any(K[i] != 0,axis=1) and np.any(K[j] != 0, axis=1):
  17.         myList.append(K[i])
  18.         print ('indices of non-similar-non-zeros rows aren',(i, j)),
  19.         else:
  20.             continue
  21.  
  22. new_K = np.asmatrix(np.asarray(myList))
  23. new_new_K = np.unique(new_K,axis=0)
  24. print('Now K is n',new_new_K)
  25.    
  26. new_new_K = [[-1.  1.  0.]
  27.                  [ 0. -1.  1.]]
  28.    
  29. import numpy as np
  30.  
  31. A = np.array([[-1,  1,  0],
  32.               [ 0,  0,  0],
  33.               [ 0, -1,  1],
  34.               [ 0,  0,  0],
  35.               [ 0, -1,  1],
  36.               [ 0,  0,  0]])
  37.  
  38. seen = set()
  39. res = []
  40.  
  41. for idx, row in enumerate(map(tuple, A)):
  42.     if row != (0, 0, 0) and row not in seen:
  43.         res.append(idx)
  44.         seen.add(row)
  45.  
  46. print(res)
  47.  
  48. # [0, 2]
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