194 lines
4.5 KiB
Python
194 lines
4.5 KiB
Python
# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.com
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Futoshiki problem in Google CP Solver.
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From http://en.wikipedia.org/wiki/Futoshiki
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'''
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The puzzle is played on a square grid, such as 5 x 5. The objective
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is to place the numbers 1 to 5 (or whatever the dimensions are)
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such that each row, and column contains each of the digits 1 to 5.
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Some digits may be given at the start. In addition, inequality
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constraints are also initially specifed between some of the squares,
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such that one must be higher or lower than its neighbour. These
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constraints must be honoured as the grid is filled out.
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'''
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Also see
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http://www.guardian.co.uk/world/2006/sep/30/japan.estheraddley
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This Google CP Solver model is inspired by the Minion/Tailor
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example futoshiki.eprime.
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Compare with the following models:
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* MiniZinc: http://hakank.org/minizinc/futoshiki.mzn
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* ECLiPSe: http://hakank.org/eclipse/futoshiki.ecl
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* Gecode: http://hakank.org/gecode/futoshiki.cpp
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* SICStus: http://hakank.org/sicstus/futoshiki.pl
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This model was created by Hakan Kjellerstrand (hakank@bonetmail.com)
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Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/
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"""
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from ortools.constraint_solver import pywrapcp
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def main(values, lt):
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# Create the solver.
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solver = pywrapcp.Solver('Futoshiki problem')
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#
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# data
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#
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size = len(values)
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RANGE = range(size)
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NUMQD = range(len(lt))
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#
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# variables
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#
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field = {}
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for i in RANGE:
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for j in RANGE:
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field[i,j] = solver.IntVar(1, size, "field[%i,%i]" % (i,j))
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field_flat = [field[i,j] for i in RANGE for j in RANGE]
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#
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# constraints
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#
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# set initial values
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for row in RANGE:
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for col in RANGE:
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if values[row][col] > 0:
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solver.Add(field[row,col] == values[row][col])
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# all rows have to be different
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for row in RANGE:
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solver.Add(solver.AllDifferent([field[row,col] for col in RANGE]))
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# all columns have to be different
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for col in RANGE:
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solver.Add(solver.AllDifferent([field[row,col] for row in RANGE]))
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# all < constraints are satisfied
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# Also: make 0-based
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for i in NUMQD:
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solver.Add(field[ lt[i][0]-1, lt[i][1]-1 ] <
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field[ lt[i][2]-1, lt[i][3]-1 ] )
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#
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# search and result
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#
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db = solver.Phase(field_flat,
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solver.CHOOSE_FIRST_UNBOUND,
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solver.ASSIGN_MIN_VALUE)
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solver.NewSearch(db)
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num_solutions = 0
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while solver.NextSolution():
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num_solutions += 1
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for i in RANGE:
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for j in RANGE:
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print field[i,j].Value(),
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print
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print
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solver.EndSearch()
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print "num_solutions:", num_solutions
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print "failures:", solver.Failures()
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print "branches:", solver.Branches()
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print "WallTime:", solver.WallTime()
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#
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# Example from Tailor model futoshiki.param/futoshiki.param
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# Solution:
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# 5 1 3 2 4
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# 1 4 2 5 3
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# 2 3 1 4 5
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# 3 5 4 1 2
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# 4 2 5 3 1
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#
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# Futoshiki instance, by Andras Salamon
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# specify the numbers in the grid
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#
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values1 = [
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[0, 0, 3, 2, 0],
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[0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0]]
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# [i1,j1, i2,j2] requires that values[i1,j1] < values[i2,j2]
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# Note: 1-based
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lt1 = [
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[1,2, 1,1],
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[1,4, 1,5],
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[2,3, 1,3],
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[3,3, 2,3],
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[3,4, 2,4],
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[2,5, 3,5],
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[3,2, 4,2],
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[4,4, 4,3],
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[5,2, 5,1],
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[5,4, 5,3],
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[5,5, 4,5]]
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#
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# Example from http://en.wikipedia.org/wiki/Futoshiki
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# Solution:
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# 5 4 3 2 1
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# 4 3 1 5 2
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# 2 1 4 3 5
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# 3 5 2 1 4
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# 1 2 5 4 3
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#
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values2 = [
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[0, 0, 0, 0, 0],
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[4, 0, 0, 0, 2],
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[0, 0, 4, 0, 0],
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[0, 0, 0, 0, 4],
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[0, 0, 0, 0, 0]]
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# Note: 1-based
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lt2 = [
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[1,2, 1,1],
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[1,4, 1,3],
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[1,5, 1,4],
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[4,4, 4,5],
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[5,1, 5,2],
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[5,2, 5,3]
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]
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if __name__ == '__main__':
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print "Problem 1"
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main(values1, lt1)
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print "\nProblem 2"
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main(values2, lt2)
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