#Constraining Order - a simple constraint satisfaction library
#
#Copyright (c) 2015 Johannes Reinhardt <jreinhardt@ist-dein-freund.de>
#
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#of this software and associated documentation files (the "Software"), to deal
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#copies of the Software, and to permit persons to whom the Software is
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#
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"""
This module defines common stuff for constraint satisfaction probleme
"""
from __future__ import unicode_literals
from builtins import object
[docs]class Space(object):
"""
A space is a description of the computation space for a specific CSP.
"""
[docs] def __init__(self,variables, constraints):
"""
Create a new Space for a CSP
:param variables: The variables of the CSP
:type variables: sequence of Variables
:param constraints: The constraints of the CSP
:type constraints: sequence of Constraints
"""
self.constraints = constraints
"list of constraints"
self.variables = {}
"dictionary of variable names to variable instances"
self.domains = {}
"dictionary of variable names to DiscreteSet/IntervalSet with admissible values"
for var in variables:
self.variables[var.name] = var
self.domains[var.name] = var.domain
[docs] def is_discrete(self):
"""
Return whether this space is discrete
"""
for domain in self.domains.values():
if not domain.is_discrete():
return False
return True
[docs] def consistent(self,lab):
"""
Check whether the labeling is consistent with all constraints
"""
for const in self.constraints:
if not const.consistent(lab):
return False
return True
[docs] def satisfied(self,lab):
"""
Check whether the labeling satisfies all constraints
"""
for const in self.constraints:
if not const.satisfied(lab):
return False
return True