Commit 871b5f25 authored by Iker Martín Álvarez's avatar Iker Martín Álvarez
Browse files

Added files used to analyse raw data

parent b2e1362b
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'''
Created on Oct 24, 2016
@author: David Llorens (dllorens@uji.es)
(c) Universitat Jaume I 2016
@license: GPL2
'''
from abc import ABCMeta, abstractmethod
infinity = float("infinity")
## Esquema para BT básico --------------------------------------------------------------------------
class PartialSolution(metaclass=ABCMeta):
@abstractmethod
def is_solution(self)-> "bool":
pass
@abstractmethod
def get_solution(self) -> "solution":
pass
@abstractmethod
def successors(self) -> "IEnumerable<PartialSolution>":
pass
class BacktrackingSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolution") -> "IEnumerable<Solution>":
def bt(ps):
if ps.is_solution():
yield ps.get_solution()
else:
for new_ps in ps.successors():
yield from bt(new_ps)
yield from bt(initial_ps)
class BacktrackingSolverOld(metaclass=ABCMeta):
def solve(self, initial_ps : "PartialSolution") -> "IEnumerable<Solution>":
def bt(ps):
if ps.is_solution():
return [ps.get_solution()]
else:
solutions = []
for new_ps in ps.successors():
solutions.extend(bt(new_ps))
return solutions
return bt(initial_ps)
## Esquema para BT con control de visitados --------------------------------------------------------
class PartialSolutionWithVisitedControl(PartialSolution):
@abstractmethod
def state(self)-> "state":
# the returned object must be of an inmutable type
pass
class BacktrackingVCSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolutionWithVisitedControl") -> "IEnumerable<Solution>":
def bt(ps):
seen.add(ps.state())
if ps.is_solution():
yield ps.get_solution()
else:
for new_ps in ps.successors():
state = new_ps.state()
if state not in seen:
yield from bt(new_ps)
seen = set()
yield from bt(initial_ps)
## Esquema para BT para optimización ----------------------------------------------------------------
class PartialSolutionWithOptimization(PartialSolutionWithVisitedControl):
@abstractmethod
def f(self)-> "int or double":
# result of applying the objective function to the partial solution
pass
class BacktrackingOptSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolutionWithOptimization") -> "IEnumerable<Solution>":
def bt(ps):
nonlocal best_solution_found_score
ps_score = ps.f()
best_seen[ps.state()] = ps_score
if ps.is_solution() and ps_score < best_solution_found_score: #sólo muestra una solución si mejora la última mostrada
best_solution_found_score = ps_score
yield ps.get_solution()
else:
for new_ps in ps.successors():
state = new_ps.state()
if state not in best_seen or new_ps.f() < best_seen[state]:
yield from bt(new_ps)
best_seen = {}
best_solution_found_score = infinity
yield from bt(initial_ps)
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