def test_lm_cut_mark_single_goal():
task = _get_intermediate_task()
heuristic = LmCutHeuristic(task)
heuristic.compute_hmax(task.initial_state)
heuristic.compute_goal_plateau(heuristic.explicit_goal)
assert {f.name
for f in heuristic.goal_plateau} == {heuristic.explicit_goal, 'g'}
def test_lm_cut_compute_single_cut():
task1 = _get_intermediate_task_two_paths()
heuristic = LmCutHeuristic(task1)
heuristic.compute_hmax(task1.initial_state)
heuristic.goal_plateau.clear()
heuristic.compute_goal_plateau(heuristic.explicit_goal)
cut = heuristic.find_cut(task1.initial_state)
assert [op.name for op in cut] == ["op4"]
def test_lm_cut_compute_single_cut():
task1 = _get_intermediate_task_two_paths()
heuristic = LmCutHeuristic(task1)
heuristic.compute_hmax(task1.initial_state)
heuristic.goal_plateau.clear()
heuristic.compute_goal_plateau(heuristic.explicit_goal)
cut = heuristic.find_cut(task1.initial_state)
assert [op.name for op in cut] == ['op4']
def test_lm_cut_mark_multiple_goal():
task = _get_intermediate_task()
heuristic = LmCutHeuristic(task)
heuristic.compute_hmax(task.initial_state)
# artificially alter operator costs to get a larger goal plateau
heuristic.relaxed_ops['op4'].cost = 0.
heuristic.compute_goal_plateau(heuristic.explicit_goal)
assert ({f.name for f in heuristic.goal_plateau} in
[{heuristic.explicit_goal, 'v4', 'g'},
{heuristic.explicit_goal, 'v5', 'g'}])
def test_two_times_hmax_same_result():
task = _get_intermediate_task()
heuristic = LmCutHeuristic(task)
heuristic.compute_hmax(task.initial_state)
heuristic.compute_hmax(task.initial_state)
# artificially alter operator costs to get a larger goal plateau
heuristic.relaxed_ops["op4"].cost = 0.0
heuristic.compute_goal_plateau(heuristic.explicit_goal)
assert {f.name for f in heuristic.goal_plateau} in [
{heuristic.explicit_goal, "v4", "g"},
{heuristic.explicit_goal, "v5", "g"},
]
def test_lm_cut_at_goal():
task = _get_simple_task_at_goal()
heuristic = LmCutHeuristic(task)
h_val = heuristic(make_root_node(task.initial_state))
heuristic.compute_goal_plateau(heuristic.explicit_goal)
assert h_val == 0.0
def test_lm_cut_at_goal():
task = _get_simple_task_at_goal()
heuristic = LmCutHeuristic(task)
h_val = heuristic(make_root_node(task.initial_state))
heuristic.compute_goal_plateau(heuristic.explicit_goal)
assert h_val == 0.
