def test_multiple_input_trajectories(self):
reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]])
reader.chunksize = 37
out = reader.get_output()
reader.chunksize = 0
out2 = reader.get_output()
expected0_2 = np.vstack((self.d, self.d))
for itraj in range(0, 3):
np.testing.assert_array_almost_equal(out[itraj], out2[itraj])
np.testing.assert_array_almost_equal(out[0], expected0_2)
np.testing.assert_array_almost_equal(out[1], self.d)
np.testing.assert_array_almost_equal(out[2], expected0_2)
def test_chunked_trajectory_random_access(self):
reader = FragmentedTrajectoryReader([self.d, self.d])
indices = np.asarray([[0, 1], [0, 3], [0, 3], [0, 99], [0, 100],
[0, 199]])
out = reader.get_output(stride=indices, chunk=1)
np.testing.assert_array_equal(
np.array(out).squeeze(), np.array([1, 3, 3, 99, 0, 99]))
def test_full_trajectory_stridden(self):
for stride in [1, 3, 5, 7, 13, 20]:
reader = FragmentedTrajectoryReader([self.d, self.d])
reader.chunksize = 0
expected = np.vstack((self.d, self.d))[::stride]
out = reader.get_output(stride=stride)[0]
np.testing.assert_array_almost_equal(expected, out, err_msg="Failed for stride=%s" % stride)
def test_multiple_input_trajectories_random_access(self):
indices = np.asarray([
[0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199],
[1, 0], [1, 5], [1, 99],
[2, 5], [2, 7], [2, 23]
])
expected = [np.array([1, 3, 3, 99, 0, 99]), np.array([0, 5, 99]), np.array([5, 7, 23])]
for chunk_size in [0, 1, 3, 5, 13]:
reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]])
out_full_trajectory_mode = reader.get_output(chunk=chunk_size, stride=indices)
for i in range(3):
np.testing.assert_array_equal(expected[i], out_full_trajectory_mode[i].squeeze())
def test_full_trajectory(self):
reader = FragmentedTrajectoryReader([self.d, self.d])
reader.chunksize = 0
expected = np.vstack((self.d, self.d))
np.testing.assert_array_almost_equal(expected,
reader.get_output(stride=1)[0])