Cost Function-Using the counter function for nonets of a Sudoku grid












0















I am currently trying to build a cost function for Sudoku. I have the following code for my random 9x9 grid assignment:



m = np.zeros((9,9)) #9x9 grid of all zeros 

vals = np.arange(1,10) #set of values from 1 to 9 aranged randomly

for i in range(0,9):

m[i,:] = np.random.choice(vals,size=9,replace=False) #randomly choses a set of 9 values for the row

print(m.astype(int)) #prints as integers


Subsequently I have created a score for the number of duplications in each column for this grid:



m = m

i = 1

for i in range(0,9):  #produces the sum of the columns score values collectively 

print(sum([r - 1 for r in Counter((m[:,i])).values()]))


I am wondering whether there is a way to produce the scores for each nonet? (each 3x3 grouping of the 9x9 Sudoku grid)



I feel like I will have to take a subsection for each 3x3 grid and then produce the duplications using the Counter function in the same way as above, but I am unsure as to how to do this.






python sudoku







share|improve this question



























    0















    I am currently trying to build a cost function for Sudoku. I have the following code for my random 9x9 grid assignment:



    m = np.zeros((9,9)) #9x9 grid of all zeros 
    
vals = np.arange(1,10) #set of values from 1 to 9 aranged randomly
    
for i in range(0,9):
    
m[i,:] = np.random.choice(vals,size=9,replace=False) #randomly choses a set of 9 values for the row
    
print(m.astype(int)) #prints as integers


    Subsequently I have created a score for the number of duplications in each column for this grid:



    m = m
    
i = 1
    
for i in range(0,9):  #produces the sum of the columns score values collectively 
    
print(sum([r - 1 for r in Counter((m[:,i])).values()]))


    I am wondering whether there is a way to produce the scores for each nonet? (each 3x3 grouping of the 9x9 Sudoku grid)



    I feel like I will have to take a subsection for each 3x3 grid and then produce the duplications using the Counter function in the same way as above, but I am unsure as to how to do this.






    python sudoku







    share|improve this question

























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      I am currently trying to build a cost function for Sudoku. I have the following code for my random 9x9 grid assignment:



      m = np.zeros((9,9)) #9x9 grid of all zeros 
      
vals = np.arange(1,10) #set of values from 1 to 9 aranged randomly
      
for i in range(0,9):
      
m[i,:] = np.random.choice(vals,size=9,replace=False) #randomly choses a set of 9 values for the row
      
print(m.astype(int)) #prints as integers


      Subsequently I have created a score for the number of duplications in each column for this grid:



      m = m
      
i = 1
      
for i in range(0,9):  #produces the sum of the columns score values collectively 
      
print(sum([r - 1 for r in Counter((m[:,i])).values()]))


      I am wondering whether there is a way to produce the scores for each nonet? (each 3x3 grouping of the 9x9 Sudoku grid)



      I feel like I will have to take a subsection for each 3x3 grid and then produce the duplications using the Counter function in the same way as above, but I am unsure as to how to do this.






      python sudoku







      share|improve this question














      I am currently trying to build a cost function for Sudoku. I have the following code for my random 9x9 grid assignment:



      m = np.zeros((9,9)) #9x9 grid of all zeros 
      
vals = np.arange(1,10) #set of values from 1 to 9 aranged randomly
      
for i in range(0,9):
      
m[i,:] = np.random.choice(vals,size=9,replace=False) #randomly choses a set of 9 values for the row
      
print(m.astype(int)) #prints as integers


      Subsequently I have created a score for the number of duplications in each column for this grid:



      m = m
      
i = 1
      
for i in range(0,9):  #produces the sum of the columns score values collectively 
      
print(sum([r - 1 for r in Counter((m[:,i])).values()]))


      I am wondering whether there is a way to produce the scores for each nonet? (each 3x3 grouping of the 9x9 Sudoku grid)



      I feel like I will have to take a subsection for each 3x3 grid and then produce the duplications using the Counter function in the same way as above, but I am unsure as to how to do this.






      python sudoku




      python sudoku






      share|improve this question













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      asked Nov 22 '18 at 10:56









      Hew.rHew.r

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