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csp.py
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csp.py
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#!/usr/bin/python
#
# Copyright (c) 2005-2014 - Gustavo Niemeyer <gustavo@niemeyer.net>
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from __future__ import absolute_import, division, print_function
import heuristic
from constraint import Solver
class RecursiveBacktrackingSolver(Solver):
"""
Recursive problem solver with backtracking capabilities
Examples:
>>> result = [[('a', 1), ('b', 2)],
... [('a', 1), ('b', 3)],
... [('a', 2), ('b', 3)]]
>>> problem = Problem(RecursiveBacktrackingSolver())
>>> problem.addVariables(["a", "b"], [1, 2, 3])
>>> problem.addConstraint(lambda a, b: b > a, ["a", "b"])
>>> solution = problem.getSolution()
>>> sorted(solution.items()) in result
True
>>> for solution in problem.getSolutions():
... sorted(solution.items()) in result
True
True
True
>>> problem.getSolutionIter()
Traceback (most recent call last):
...
NotImplementedError: RecursiveBacktrackingSolver doesn't provide iteration
"""
def __init__(self, forwardcheck=True):
"""
@param forwardcheck: If false forward checking will not be requested
to constraints while looking for solutions
(default is true)
@type forwardcheck: bool
"""
self._forwardcheck = forwardcheck
def recursiveBacktracking(
self, solutions, domains, vconstraints, assignments, single
):
# assignments is a dictionary of {variable: value, ...}
##############################################################
# Use different heuristics for selecting unassigned variable #
##############################################################
lst = heuristic.variable_heuristic(domains, vconstraints, 'mrv')
for item in lst:
if item[-1] not in assignments:
# Found an unassigned variable. Let's go.
break
else:
# No unassigned variables. We've got a solution.
solutions.append(assignments.copy())
return solutions
variable = item[-1]
assignments[variable] = None
forwardcheck = self._forwardcheck
if forwardcheck:
pushdomains = [domains[x] for x in domains if x not in assignments]
else:
pushdomains = None
################################################
# Change heuristics for order of domain values #
################################################
newlst = heuristic.value_heuristic(assignments, domains, domains[variable], 'none')
for value in newlst:
assignments[variable] = value
if pushdomains:
for domain in pushdomains:
domain.pushState()
for constraint, variables in vconstraints[variable]:
if not constraint(variables, domains, assignments, pushdomains):
# Value is not good.
break
else:
# Value is good. Recurse and get next variable.
self.recursiveBacktracking(
solutions, domains, vconstraints, assignments, single
)
if solutions and single:
return solutions
if pushdomains:
for domain in pushdomains:
domain.popState()
del assignments[variable]
return solutions
def getSolution(self, domains, constraints, vconstraints):
solutions = self.recursiveBacktracking([], domains, vconstraints, {}, True)
return solutions and solutions[0] or None
def getSolutions(self, domains, constraints, vconstraints):
return self.recursiveBacktracking([], domains, vconstraints, {}, False)