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# Copyright 2010 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.
"""
Young tableaux in Google CP Solver.
See
http://mathworld.wolfram.com/YoungTableau.html
and
http://en.wikipedia.org/wiki/Young_tableau
'''
The partitions of 4 are
{4}, {3,1}, {2,2}, {2,1,1}, {1,1,1,1}
And the corresponding standard Young tableaux are:
1. 1 2 3 4
2. 1 2 3 1 2 4 1 3 4
4 3 2
3. 1 2 1 3
3 4 2 4
4 1 2 1 3 1 4
3 2 2
4 4 3
5. 1
2
3
4
'''
Thanks to Laurent Perron for improving this model.
Compare with the following models:
* MiniZinc: http://www.hakank.org/minizinc/young_tableaux.mzn
* Choco : http://www.hakank.org/choco/YoungTableuax.java
* JaCoP : http://www.hakank.org/JaCoP/YoungTableuax.java
* Comet : http://www.hakank.org/comet/young_tableaux.co
* Gecode : http://www.hakank.org/gecode/young_tableaux.cpp
* ECLiPSe : http://www.hakank.org/eclipse/young_tableaux.ecl
* Tailor/Essence' : http://www.hakank.org/tailor/young_tableaux.eprime
* SICStus: http://hakank.org/sicstus/young_tableaux.pl
* Zinc: http://hakank.org/minizinc/young_tableaux.zinc
This model was created by Hakan Kjellerstrand (hakank@gmail.com)
Also see my other Google CP Solver models:
http://www.hakank.org/google_or_tools/
"""
from __future__ import print_function
import sys
from ortools.constraint_solver import pywrapcp
# Create the solver.
solver = pywrapcp.Solver("Problem")
#
# data
#
print("n:", n)
#
# declare variables
#
x = {}
for i in range(n):
for j in range(n):
x[(i, j)] = solver.IntVar(1, n + 1, "x(%i,%i)" % (i, j))
x_flat = [x[(i, j)] for i in range(n) for j in range(n)]
# partition structure
p = [solver.IntVar(0, n + 1, "p%i" % i) for i in range(n)]
#
# constraints
#
# 1..n is used exactly once
for i in range(1, n + 1):
solver.Add(solver.Count(x_flat, i, 1))
solver.Add(x[(0, 0)] == 1)
# row wise
for i in range(n):
for j in range(1, n):
solver.Add(x[(i, j)] >= x[(i, j - 1)])
# column wise
for j in range(n):
for i in range(1, n):
solver.Add(x[(i, j)] >= x[(i - 1, j)])
# calculate the structure (the partition)
for i in range(n):
# MiniZinc/Zinc version:
# p[i] == sum(j in 1..n) (bool2int(x[i,j] <= n))
b = [solver.IsLessOrEqualCstVar(x[(i, j)], n) for j in range(n)]
solver.Add(p[i] == solver.Sum(b))
solver.Add(solver.Sum(p) == n)
for i in range(1, n):
solver.Add(p[i - 1] >= p[i])
#
# solution and search
#
solution = solver.Assignment()
solution.Add(x_flat)
solution.Add(p)
# db: DecisionBuilder
db = solver.Phase(x_flat + p, solver.CHOOSE_FIRST_UNBOUND,
solver.ASSIGN_MIN_VALUE)
solver.NewSearch(db)
num_solutions = 0
while solver.NextSolution():
print("p:", [p[i].Value() for i in range(n)])
print("x:")
for i in range(n):
for j in range(n):
val = x_flat[i * n + j].Value()
if val <= n:
print(val, end=" ")
if p[i].Value() > 0:
print()
print()
num_solutions += 1
solver.EndSearch()
print()
print("num_solutions:", num_solutions)
print("failures:", solver.Failures())
print("branches:", solver.Branches())
print("WallTime:", solver.WallTime())
n = 5