def perf_ngsim_env_step():
basedir = os.path.expanduser('~/.julia/packages/NGSIM/9OYUa/data')
filename = 'trajdata_i101_trajectories-0750am-0805am.txt'
filepaths = [os.path.join(basedir, filename)]
env = JuliaEnv(env_id='NGSIMEnv',
env_params=dict(trajectory_filepaths=filepaths, ),
using='AutoEnvs')
n_steps = 10000
action = np.array([1., 0.])
env.reset()
with ContextTimer():
for _ in range(n_steps):
_, _, terminal, _ = env.step(action)
if terminal:
env.reset()
def test_ngsim_env(self):
basedir = os.path.expanduser('~/.julia/packages/NGSIM/9OYUa/data')
filename = 'trajdata_i80_trajectories-0400-0415.txt'
filepaths = [os.path.join(basedir, filename)]
env = JuliaEnv(env_id='NGSIMEnv',
env_params=dict(trajectory_filepaths=filepaths),
using='AutoEnvs')
x = env.reset()
nx, r, t, info = env.step(np.array([0., 0.]))
self.assertTrue(np.sum(np.abs(x - nx)) > 1e-1)
# complex reset
x = env.reset(offset=250, egoid=3194, start=8886)
nx = env.reset(offset=250, egoid=3194, start=8886)
np.testing.assert_array_almost_equal(x, nx, 4)
def perf_vectorized_ngsim_env_step():
basedir = os.path.expanduser('~/.julia/packages/NGSIM/9OYUa/data')
filename = 'trajdata_i101_trajectories-0750am-0805am.txt'
filepaths = [os.path.join(basedir, filename)]
n_envs = 100
env = JuliaEnv(env_id='VectorizedNGSIMEnv',
env_params=dict(
n_envs=n_envs,
trajectory_filepaths=filepaths,
),
using='AutoEnvs')
n_steps = 10000
action = np.zeros((n_envs, 2))
action[:, 0] = 1.
env.reset()
with ContextTimer():
for _ in range(0, n_steps, n_envs):
_, _, terminal, _ = env.step(action)
env.reset(terminal)
def test_julia_env(self):
env = JuliaEnv(env_id='DeterministicSingleStepDebugEnv',
env_params={},
using='AutoEnvs')
x = env.reset()
nx, r, t, info = env.step(1)
self.assertEqual(x, 0)
self.assertEqual(nx, 0)
self.assertEqual(r, 1)
self.assertEqual(t, True)