def test_minimizeB1(self):
"""Beam Search optimisation problem (longer) (beam=3, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
goalstate = InformedReorderSearchState("This is supposed to be a very long sentence .".split(' '))
informedinputstate = InformedReorderSearchState("a long very . sentence supposed to be This is".split(' '), goalstate)
search = BeamSearch(informedinputstate, beamsize=3, graph=True, minimize=True,debug=False)
solution = search.searchbest()
self.assertEqual(str(solution),str(goalstate))
def test_minimizeA1(self):
"""Beam Search optimisation problem A (beam=2, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate, beamsize=2, graph=True, minimize=True,debug=0)
solution = search.searchbest()
self.assertEqual( str(solution), str(goalstate) )
self.assertTrue( search.solutions > 1 ) #everything is a solution
def test_minimizeA2(self):
"""Beam Search optimisation problem A (beam=100, minimize)"""
#if a small beamsize works, a very large one should too
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate, beamsize=100, graph=True, minimize=True,debug=0)
solution = search.searchbest()
self.assertEqual( str(solution), str(goalstate) )
self.assertTrue( search.solutions > 1 ) #everything is a solution
def test_minimizeC1(self):
"""Beam Search needle-in-haystack problem (beam=2, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate, beamsize=2, graph=True, minimize=True,debug=0, goal=goalstate)
solution = search.searchbest()
self.assertEqual( str(solution), str(goalstate) )
self.assertEqual( search.solutions, 1 )
def test_minimizeA2(self):
"""Beam Search optimisation problem A (beam=100, minimize)"""
#if a small beamsize works, a very large one should too
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate,
beamsize=100,
graph=True,
minimize=True,
debug=0)
solution = search.searchbest()
self.assertEqual(str(solution), str(goalstate))
self.assertTrue(search.solutions > 1) #everything is a solution
def test_minimizeA1(self):
"""Beam Search optimisation problem A (beam=2, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate,
beamsize=2,
graph=True,
minimize=True,
debug=0)
solution = search.searchbest()
self.assertEqual(str(solution), str(goalstate))
self.assertTrue(search.solutions > 1) #everything is a solution
def test_minimizeC1(self):
"""Beam Search needle-in-haystack problem (beam=2, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
global informedinputstate, solution, goalstate
search = BeamSearch(informedinputstate,
beamsize=2,
graph=True,
minimize=True,
debug=0,
goal=goalstate)
solution = search.searchbest()
self.assertEqual(str(solution), str(goalstate))
self.assertEqual(search.solutions, 1)
def test_minimizeB1(self):
"""Beam Search optimisation problem (longer) (beam=3, minimize)"""
#beamsize has been set to the minimum that yields the correct solution
goalstate = InformedReorderSearchState(
"This is supposed to be a very long sentence .".split(' '))
informedinputstate = InformedReorderSearchState(
"a long very . sentence supposed to be This is".split(' '),
goalstate)
search = BeamSearch(informedinputstate,
beamsize=3,
graph=True,
minimize=True,
debug=False)
solution = search.searchbest()
self.assertEqual(str(solution), str(goalstate))