def test_juelich_12_obstructed_visibility(tmp_path, env, operational_model_id):
"""
Four pedestrians being simulated in a bottleneck. Pedestrians 0 and 1 have
zero desired speed i.e. they will not move during the simulation whereas
pedestrians 2 and 3 are heading towards the exit.
The visibility between pedestrians 2 resp. 3 and 0 resp. 2 is obstructed
by a wall resp. an obstacle.
Expected results: Pedestrians 2 and 3 should not deviate from
the horizontal dashed line.
:param tmp_path: working directory of test execution
:param env: global environment object
"""
input_location = env.systemtest_path / "juelich_tests" / "test_12"
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={"operational_model_id": operational_model_id},
dest=inifile_path,
)
copy_files(
sources=[input_location / "geometry.xml"],
dest=tmp_path,
)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
agent_path = trajectories.path(2)
y = agent_path[:, 3]
dy = numpy.sum(numpy.abs(numpy.diff(y)))
tolerance = 0.005
assert dy < tolerance
def test_router_corridor_close(tmp_path, env, router_id):
"""
:param tmp_path: working directory of test execution
:param env: global environment object
"""
input_location = (env.systemtest_path / "router_tests" /
"test_corridor_close")
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={"router_id": router_id},
dest=inifile_path,
)
copy_files(
sources=[input_location / "geometry.xml"],
dest=tmp_path,
)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
agent_path = trajectories.path(2)
assert get_intersetions_path_segment(
agent_path, Segment(Point(9.5, -5), Point(9.5, 5)))
def test_juelich_8_obstacle_avoidance(tmp_path, env, operational_model_id):
"""
Expected result: The pedestrian should avoid the obstacle and exit the room
without overlapping with the obstacle.
:param tmp_path: working directory of test execution
:param env: global environment object
"""
input_location = env.systemtest_path / "juelich_tests" / "test_8"
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={"operational_model_id": operational_model_id},
dest=inifile_path,
)
copy_files(
sources=[input_location / "geometry.xml"],
dest=tmp_path,
)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
assert trajectories.runtime() <= 45.0
def test_juelich_3_single_pedestrian_moving_in_a_corridor_with_a_desired_direction(
tmp_path, env, seed, exit_crossing_strategy):
"""
A pedestrian is started from a random position in a holding area. This test
should be repeated with different initial positions. Expected result: The
pedestrians should be able to reach the marked goal in all repetitions of
the test.
:param tmp_path: working directory of test execution
:param env: global environment object
:param seed: value to use for the simulation
:param exit_crossing_strategy: exit strategy id to use
"""
input_location = env.systemtest_path / "juelich_tests" / "test_3"
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={
"seed": seed,
"exit_crossing_strategy": exit_crossing_strategy
},
dest=inifile_path,
)
copy_files(sources=[input_location / "geometry.xml"], dest=tmp_path)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
agent_path = trajectories.path(2)
assert trajectories.runtime() < 10.0
assert numpy.any(agent_path[:, 2] > 8.5)
def test_juelich_2_single_pedestrian_moving_in_a_corridor(
tmp_path, env, operational_model_id):
"""
Rotating the same geometry as in test 1 around the z−axis by an arbitrary angle e.g.
45deg should lead to the evacuation time of 10 s.
:param tmp_path: working directory of test execution
:param env: global environment object
:param operational_model_id this test is parametrized for two models, the
ids have to match the model ids in the template file
"""
input_location = env.systemtest_path / "juelich_tests" / "test_2"
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={"operational_model_id": operational_model_id},
dest=inifile_path,
)
copy_files(sources=[input_location / "geometry.xml"], dest=tmp_path)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
agent_path = trajectories.path(2)
d_x = max(agent_path[:, 2]) - min(agent_path[:, 2])
d_y = max(agent_path[:, 3]) - min(agent_path[:, 3])
beeline_distance = numpy.sqrt(d_x**2 + d_y**2)
v_expected = 1.0
time_limit = (beeline_distance / v_expected) + 0.1
assert trajectories.runtime() <= time_limit
def test_juelich_11_geo_room_subroom_structure(tmp_path, env,
operational_model_id):
"""
The same geometry is constructed differently The whole geometry is designed
as a rooms (i.e. utility space) The geometry is designed by dividing the
utility space in connected subrooms. Distribute randomly pedestrians in all
sub-rooms of the geometry and repeat the simulation to get a certain
statistical significance.
Expected results: The mean value of the evacuation times calculated from
both cases should not differ.
:param tmp_path: working directory of test execution
:param env: global environment object
"""
input_location = env.systemtest_path / "juelich_tests" / "test_11"
template_path_a = input_location / "inifile_a.template"
template_path_b = input_location / "inifile_b.template"
tmp_path_a = tmp_path / "a"
tmp_path_b = tmp_path / "b"
tmp_path_a.mkdir()
tmp_path_b.mkdir()
inifile_path_a = tmp_path_a / "inifile.xml"
instanciate_tempalte(
src=template_path_a,
args={"operational_model_id": operational_model_id},
dest=inifile_path_a,
)
copy_files(
sources=[input_location / "geometry_a.xml"],
dest=tmp_path_a,
)
inifile_path_b = tmp_path_b / "inifile.xml"
instanciate_tempalte(
src=template_path_b,
args={"operational_model_id": operational_model_id},
dest=inifile_path_b,
)
copy_files(
sources=[input_location / "geometry_b.xml"],
dest=tmp_path_b,
)
jpscore_driver_a = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path_a)
jpscore_driver_a.run()
jpscore_driver_b = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path_b)
jpscore_driver_b.run()
trajectories_a = load_trajectory(jpscore_driver_a.traj_file)
trajectories_b = load_trajectory(jpscore_driver_b.traj_file)
assert numpy.allclose(trajectories_a.data, trajectories_b.data, 0.001)
def test_juelich_4_single_pedestrian_moving_in_a_corridor_with_obstacle(
tmp_path, env, operational_model_id):
"""
Two pedestrians are aligned in the same room. The second pedestrian from left is standing and will not move during the test.
Expected result: Pedestrian left should be able to overtake the standing pedestrian.
:param tmp_path: working directory of test execution
:param env: global environment object
:param operational_model_id this test is parametrized for two models, the
ids have to match the model ids in the template file
"""
input_location = env.systemtest_path / "juelich_tests" / "test_4"
template_path = input_location / "inifile.template"
inifile_path = tmp_path / "inifile.xml"
instanciate_tempalte(
src=template_path,
args={"operational_model_id": operational_model_id},
dest=inifile_path,
)
copy_files(sources=[input_location / "geometry.xml"], dest=tmp_path)
jpscore_driver = JpsCoreDriver(jpscore_path=env.jpscore_path,
working_directory=tmp_path)
jpscore_driver.run()
trajectories = load_trajectory(jpscore_driver.traj_file)
agent_path3 = trajectories.path(3)
agent_path4 = trajectories.path(4)
x_1 = agent_path3[:, 2]
y_1 = agent_path3[:, 3]
x_2 = agent_path4[:, 2]
y_2 = agent_path4[:, 3]
eps = 0.3 # 10 cm
x_min = x_2[0] - eps
x_max = x_2[0] + eps
y_min = y_2[0] - eps
y_max = y_2[0] + eps
lx = numpy.logical_and(x_1 > x_min, x_1 < x_max)
ly = numpy.logical_and(y_1 > y_min, y_1 < y_max)
overlap = (lx * ly).any()
assert not overlap
