# Copyright 2021 Hakan Kjellerstrand hakank@gmail.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""

  Killer Sudoku in OR-tools CP-SAT Solver.

  http://en.wikipedia.org/wiki/Killer_Sudoku
  '''
  Killer sudoku (also killer su doku, sumdoku, sum doku, addoku, or
  samunamupure) is a puzzle that combines elements of sudoku and kakuro.
  Despite the name, the simpler killer sudokus can be easier to solve
  than regular sudokus, depending on the solver's skill at mental arithmetic;
  the hardest ones, however, can take hours to crack.

  ...

  The objective is to fill the grid with numbers from 1 to 9 in a way that
  the following conditions are met:

    * Each row, column, and nonet contains each number exactly once.
    * The sum of all numbers in a cage must match the small number printed
      in its corner.
    * No number appears more than once in a cage. (This is the standard rule
      for killer sudokus, and implies that no cage can include more
      than 9 cells.)

  In 'Killer X', an additional rule is that each of the long diagonals
  contains each number once.
  '''

  Here we solve the problem from the Wikipedia page, also shown here
  http://en.wikipedia.org/wiki/File:Killersudoku_color.svg

  The output is:
    2 1 5 6 4 7 3 9 8
    3 6 8 9 5 2 1 7 4
    7 9 4 3 8 1 6 5 2
    5 8 6 2 7 4 9 3 1
    1 4 2 5 9 3 8 6 7
    9 7 3 8 1 6 4 2 5
    8 2 1 7 3 9 5 4 6
    6 5 9 4 2 8 7 1 3
    4 3 7 1 6 5 2 8 9

  This is a port of my old CP model killer_sudoky.py


  This model was created by Hakan Kjellerstrand (hakank@gmail.com)
  Also see my other OR-tools models: http://www.hakank.org/or_tools/
"""
from __future__ import print_function
from ortools.sat.python import cp_model as cp
import math, sys
# from cp_sat_utils import *

#
# Ensure that the sum of the segments
# in cc == res
#
def calc(model, cc, x, res):

  # sum the numbers
  cage = [x[i[0] - 1, i[1] - 1] for i in cc]
  model.Add(sum(cage) == res)
  model.AddAllDifferent(cage)


def main():

  model = cp.CpModel()

  #
  # data
  #

  # size of matrix
  n = 9

  # For a better view of the problem, see
  #  http://en.wikipedia.org/wiki/File:Killersudoku_color.svg

  # hints
  #    [sum, [segments]]
  # Note: 1-based
  problem = [[3, [[1, 1], [1, 2]]], [15, [[1, 3], [1, 4], [1, 5]]],
             [22, [[1, 6], [2, 5], [2, 6], [3, 5]]], [4, [[1, 7], [2, 7]]],
             [16, [[1, 8], [2, 8]]], [15, [[1, 9], [2, 9], [3, 9], [4, 9]]],
             [25, [[2, 1], [2, 2], [3, 1], [3, 2]]], [17, [[2, 3], [2, 4]]],
             [9, [[3, 3], [3, 4], [4, 4]]], [8, [[3, 6], [4, 6], [5, 6]]],
             [20, [[3, 7], [3, 8], [4, 7]]], [6, [[4, 1], [5, 1]]],
             [14, [[4, 2], [4, 3]]], [17, [[4, 5], [5, 5], [6, 5]]],
             [17, [[4, 8], [5, 7], [5, 8]]], [13, [[5, 2], [5, 3], [6, 2]]],
             [20, [[5, 4], [6, 4], [7, 4]]], [12, [[5, 9], [6, 9]]],
             [27, [[6, 1], [7, 1], [8, 1], [9, 1]]],
             [6, [[6, 3], [7, 2], [7, 3]]], [20, [[6, 6], [7, 6], [7, 7]]],
             [6, [[6, 7], [6, 8]]], [10, [[7, 5], [8, 4], [8, 5], [9, 4]]],
             [14, [[7, 8], [7, 9], [8, 8], [8, 9]]], [8, [[8, 2], [9, 2]]],
             [16, [[8, 3], [9, 3]]], [15, [[8, 6], [8, 7]]],
             [13, [[9, 5], [9, 6], [9, 7]]], [17, [[9, 8], [9, 9]]]]

  #
  # variables
  #

  # the set
  x = {}
  for i in range(n):
    for j in range(n):
      x[i, j] = model.NewIntVar(1, n, "x[%i,%i]" % (i, j))

  x_flat = [x[i, j] for i in range(n) for j in range(n)]

  #
  # constraints
  #

  # all rows and columns must be unique
  for i in range(n):
    row = [x[i, j] for j in range(n)]
    model.AddAllDifferent(row)

    col = [x[j, i] for j in range(n)]
    model.AddAllDifferent(col)

  # cells
  for i in range(2):
    for j in range(2):
      cell = [
          x[r, c]
          for r in range(i * 3, i * 3 + 3)
          for c in range(j * 3, j * 3 + 3)
      ]
      model.AddAllDifferent(cell)

  # calculate the segments
  for (res, segment) in problem:
    calc(model,segment, x, res)

  #
  # search and solution
  #
  solver = cp.CpSolver() 
  status = solver.Solve(model)

  if status == cp.OPTIMAL:
    for i in range(n):
      for j in range(n):
        print(solver.Value(x[i, j]), end=" ")
      print()
    print()

  print("NumConflicts:", solver.NumConflicts())
  print("NumBranches:", solver.NumBranches())
  print("WallTime:", solver.WallTime())


if __name__ == "__main__":
  main()