def test_discrete(self) -> None:
""" DISCRETE """
self.cfg["angle_cost_function"] = "discrete"
self.cfg["max_angle"] = np.pi / 4
self.cfg["angle_weight"] = .3
graph = AngleGraph(self.instance, self.corridor)
_ = graph.single_sp(**self.cfg)
gt_angle_cost_arr = graph.angle_cost_array.copy()
gt_dists = graph.dists.copy()
graph.dists = np.zeros(
(len(graph.stack_array), len(graph.shifts))
) + np.inf
graph.dists[0, :] = 0
graph.preds = np.zeros(graph.dists.shape) - 1
graph.angle_cost_function = "some_non_existant"
graph.build_source_sp_tree(**self.cfg)
self.assertTrue(np.all(gt_angle_cost_arr == graph.angle_cost_array))
self.assertTrue(np.all(np.isclose(gt_dists, graph.dists)))
def test_linear(self) -> None:
""" LINEAR """
self.cfg["angle_cost_function"] = "linear"
self.cfg["max_angle"] = np.pi
self.cfg["angle_weight"] = .3
graph = AngleGraph(self.instance, self.corridor)
_ = graph.single_sp(**self.cfg)
gt_angle_cost_arr = graph.angle_cost_array.copy()
gt_dists = graph.dists.copy()
graph.dists = np.zeros(
(len(graph.stack_array), len(graph.shifts))
) + np.inf
graph.dists[0, :] = 0
graph.preds = np.zeros(graph.dists.shape) - 1
graph.angle_cost_function = "some_non_existant"
graph.build_source_sp_tree(**self.cfg)
self.assertTrue(
np.all(np.isclose(gt_angle_cost_arr, graph.angle_cost_array))
)
# Errors can occur randomly, but seem to be only precision errors
# errors only appear if angle_weight > 0, try 1 to reproduce
self.assertTrue(np.all(np.isclose(gt_dists, graph.dists, atol=1e-04)))