def test_inputs():
horizon, theta, deadline, solver_type = get_solver_param()
g, v0_target, v0_searchers, target_motion, belief_distribution = parameters_sim()
specs = MyInputs()
specs.set_theta(theta)
specs.set_deadline(deadline)
specs.set_solver_type(solver_type)
specs.set_horizon(horizon)
specs.set_graph(0)
specs.set_start_target(v0_target)
specs.set_start_searchers(v0_searchers)
specs.set_target_motion(target_motion)
specs.set_belief_distribution(belief_distribution)
assert g["name"] == specs.graph["name"]
assert specs.horizon == horizon
assert specs.theta == theta
assert specs.start_target_random is False
assert specs.start_target_true == v0_target[0]
assert specs.start_searcher_random is False
assert specs.start_searcher_v == v0_searchers
assert specs.target_motion == target_motion
assert specs.belief_distribution == belief_distribution
def my_specs():
theta = 2
deadline = 6
horizon = 3
solver_type = 'central'
graph_file = 'G7V_test.p'
g = ext.get_graph(graph_file)
target_motion = 'random'
belief_distribution = 'uniform'
v0_target = [7]
v0_searchers = [1, 2]
specs = MyInputs()
specs.set_graph(0)
specs.set_theta(theta)
specs.set_deadline(deadline)
specs.set_solver_type(solver_type)
specs.set_horizon(horizon)
specs.set_start_target(v0_target)
specs.set_start_searchers(v0_searchers)
specs.set_target_motion(target_motion)
specs.set_belief_distribution(belief_distribution)
return specs
def my_specs():
horizon, theta, deadline, solver_type = get_solver_param()
g, v0_target, v0_searchers, target_motion, belief_distribution = parameters_sim()
specs = MyInputs()
specs.set_graph(0)
specs.set_theta(theta)
specs.set_deadline(deadline)
specs.set_solver_type(solver_type)
specs.set_horizon(horizon)
specs.set_start_target(v0_target)
specs.set_start_searchers(v0_searchers)
specs.set_target_motion(target_motion)
specs.set_belief_distribution(belief_distribution)
return specs