class TrajectoryDataset¶
- class deeptime.util.data.TrajectoryDataset(lagtime, trajectory)¶
Creates a trajectory dataset from a single trajectory by applying a lagtime.
- Parameters:
lagtime (int) – Lagtime, must be positive. The effective size of the dataset reduces by the selected lagtime.
trajectory ((T, d) ndarray) – Trajectory with T frames in d dimensions.
- Raises:
AssertionError – If lagtime is not positive or trajectory is too short for lagtime.
Attributes
Instantaneous data.
Time-lagged data.
lagtime
trajectory
Methods
astype
(dtype)Sets the datatype of contained arrays and returns a new instance of TimeLaggedDataset.
from_trajectories
(lagtime, data)Creates a time series dataset from multiples trajectories by applying a lagtime.
setflags
([write])Set writeable flags for contained arrays.
- astype(dtype)¶
Sets the datatype of contained arrays and returns a new instance of TimeLaggedDataset.
- Parameters:
dtype – The new dtype.
- Returns:
converted_ds – The dataset with converted dtype.
- Return type:
- static from_trajectories(lagtime, data: List[ndarray])¶
Creates a time series dataset from multiples trajectories by applying a lagtime.
- Parameters:
lagtime (int) – Lagtime, must be positive. The effective size of the dataset reduces by the selected lagtime.
data (list of ndarray) – List of trajectories.
- Returns:
dataset – Concatenation of timeseries datasets.
- Return type:
- Raises:
AssertionError – If data is empty, lagtime is not positive, the shapes do not match, or lagtime is too long for all of the trajectories.
- setflags(write=True)¶
Set writeable flags for contained arrays.
- property data: ndarray¶
Instantaneous data.
- property data_lagged: ndarray¶
Time-lagged data.