def test1dData(self):
n = 3
data = np.arange(n)
reader = DataInMemory(data)
self.assertEqual(reader.trajectory_lengths(), np.array([n]))
self.assertEqual(reader.ndim, 1)
self.assertEqual(reader.number_of_trajectories(), 1)
self.assertEqual(reader.n_frames_total(), n)
def test1dDataList(self):
n = 10
data = [np.arange(n), np.arange(n)]
reader = DataInMemory(data)
np.testing.assert_equal(reader.trajectory_lengths(), np.array([n, n]))
self.assertEqual(reader.ndim, 1)
self.assertEqual(reader.number_of_trajectories(), 2)
self.assertEqual(reader.n_frames_total(), 2 * n)
def test1dDataList(self):
n = 10
data = [np.arange(n), np.arange(n)]
reader = DataInMemory(data)
self.assertEqual(reader.trajectory_lengths(), [n, n])
self.assertEqual(reader.dimension(), 1)
self.assertEqual(reader.number_of_trajectories(), 2)
self.assertEqual(reader.n_frames_total(), 2 * n)
def test1dData(self):
n = 3
data = np.arange(n)
reader = DataInMemory(data)
self.assertEqual(reader.trajectory_lengths(), [n])
self.assertEqual(reader.dimension(), 1)
self.assertEqual(reader.number_of_trajectories(), 1)
self.assertEqual(reader.n_frames_total(), n)
def test_ndim_input(self):
data = np.empty((4, 2, 2, 2))
reader = DataInMemory(data)
self.assertEqual(reader.ndim, 2 * 2 * 2)
self.assertEqual(reader.number_of_trajectories(), 1)
self.assertEqual(reader.n_frames_total(), 4)
np.testing.assert_equal(reader.trajectory_lengths(),
np.array([reader.n_frames_total()]))
def test_ndim_input(self):
data = np.empty((4, 2, 2, 2))
reader = DataInMemory(data)
self.assertEqual(reader.dimension(), 2 * 2 * 2)
self.assertEqual(reader.number_of_trajectories(), 1)
self.assertEqual(reader.n_frames_total(), 4)
self.assertEqual(
reader.trajectory_lengths(), [reader.n_frames_total()])
def test_time_lagged_chunked_access(self):
n = 100
data = [
np.random.random((n, 3)),
np.zeros((29, 3)),
np.random.random((n - 50, 3))
]
reader = DataInMemory(data)
self.assertEqual(reader.n_frames_total(), n + n - 50 + 29)
# iterate over data
ctx = TransformerIteratorContext(lag=30)
t = 0
itraj = 0
last_chunk = False
while not last_chunk:
last_chunk_in_traj = False
t = 0
while not last_chunk_in_traj:
X, Y = reader._next_chunk(ctx)
if itraj == 0:
self.assertEqual(X.shape, (100, 3))
self.assertEqual(Y.shape, (70, 3))
elif itraj == 1:
# the time lagged chunk can not be built due to lag time
self.assertEqual(X.shape, (29, 3))
self.assertEqual(Y.shape, (0, 3))
elif itraj == 2:
self.assertEqual(X.shape, (50, 3))
self.assertEqual(Y.shape, (20, 3))
L = np.shape(X)[0]
# last chunk in traj?
last_chunk_in_traj = (t + L >= reader.trajectory_length(itraj))
# last chunk?
last_chunk = (last_chunk_in_traj
and itraj >= reader.number_of_trajectories() - 1)
t += L
# increment trajectory
itraj += 1
def test_time_lagged_chunked_access(self):
n = 100
data = [np.random.random((n, 3)), np.zeros((29, 3)),
np.random.random((n - 50, 3))]
reader = DataInMemory(data)
self.assertEqual(reader.n_frames_total(), n + n - 50 + 29)
# iterate over data
lag = 30
t = 0
itraj = 0
last_chunk = False
while not last_chunk:
last_chunk_in_traj = False
t = 0
while not last_chunk_in_traj:
X, Y = reader._next_chunk(lag=lag)
if itraj == 0:
self.assertEqual(X.shape, (100, 3))
self.assertEqual(Y.shape, (70, 3))
elif itraj == 1:
# the time lagged chunk can not be built due to lag time
self.assertEqual(X.shape, (29, 3))
self.assertEqual(Y.shape, (0, 3))
elif itraj == 2:
self.assertEqual(X.shape, (50, 3))
self.assertEqual(Y.shape, (20, 3))
L = np.shape(X)[0]
# last chunk in traj?
last_chunk_in_traj = (
t + L >= reader.trajectory_length(itraj))
# last chunk?
last_chunk = (
last_chunk_in_traj and itraj >= reader.number_of_trajectories() - 1)
t += L
# increment trajectory
itraj += 1
