mdtraj.TRRTrajectoryFile

class mdtraj.TRRTrajectoryFile

Interface for reading and writing to a GROMACS TRR file. This is a file-like objec that supports both reading and writing. It also supports the context manager protocol, so you can use it with the python ‘with’ statement.

The conventional units in the TRR file are nanometers and picoseconds. The format only supports saving coordinates, the time, the md step, and the unit cell parametrs (box vectors)

Parameters:

filename : str

The filename to open. A path to a file on disk.

mode : {‘r’, ‘w’}

The mode in which to open the file, either ‘r’ for read or ‘w’ for write.

force_overwrite : bool

If opened in write mode, and a file by the name of filename already exists on disk, should we overwrite it?
Other Parameters:
 

min_chunk_size : int, default=100

In read mode, we need to allocate a buffer in which to store the data without knowing how many frames are in the file. This parameter is the minimum size of the buffer to allocate.

chunk_size_multiplier, int, default=1.5

In read mode, we need to allocate a buffer in which to store the data without knowing how many frames are in the file. We can guess this information based on the size of the file on disk, but it’s not perfect. This parameter inflates the guess by a multiplicative factor.

See also

mdtraj.load_trr
High-level wrapper that returns a md.Trajectory

Examples

>>> # load up the data from a trr
>>> with XTCTrajectoryFile('traj.trr') as f:
>>>    xyz, time, step, box, lambdas = f.read()
__init__()

x.__init__(...) initializes x; see help(type(x)) for signature

Methods

close Close the TRR file
read([n_frames, stride, atom_indices]) Read data from a TRR file
seek Move to a new file position
tell Current file position
write(xyz[, time, step, box, lambd]) Write data to a TRR file

Attributes

distance_unit
close()

Close the TRR file

read(n_frames=None, stride=None, atom_indices=None)

Read data from a TRR file

Parameters:

n_frames : int, None

The number of frames you would like to read from the file. If None, all of the remaining frames will be loaded.

stride : int, optional

Read only every stride-th frame.

atom_indices : array_like, optional

If not none, then read only a subset of the atoms coordinates from the file. This may be slightly slower than the standard read because it required an extra copy, but will save memory.
Returns:

xyz : np.ndarray, shape=(n_frames, n_atoms, 3), dtype=np.float32

The cartesian coordinates, in nanometers

time : np.ndarray, shape=(n_frames), dtype=np.float32

The simulation time, in picoseconds, corresponding to each frame

step : np.ndarray, shape=(n_frames), dtype=np.int32

The step in the simulation corresponding to each frame

box : np.ndarray, shape=(n_frames, 3, 3), dtype=np.float32

The box vectors in each frame.

lambd : np.ndarray, shape=(n_frames), dtype=np.float32

The alchemical lambda value of each frame.
seek()

Move to a new file position

Parameters:

offset : int

A number of frames.

whence : {0, 1, 2}

0: offset from start of file, offset should be >=0. 1: move relative to the current position, positive or negative 2: move relative to the end of file, offset should be <= 0. Seeking beyond the end of a file is not supported
tell()

Current file position

Returns:

offset : int

The current frame in the file.
write(xyz, time=None, step=None, box=None, lambd=None)

Write data to a TRR file

Parameters:

xyz : np.ndarray, dtype=np.float32, shape=(n_frames, n_atoms, 3)

The cartesian coordinates of the atoms, in nanometers

time : np.ndarray, dtype=float32, shape=(n_frames), optional

The simulation time corresponding to each frame, in picoseconds. If not supplied, the numbers 0..n_frames will be written.

step : np.ndarray, dtype=int32, shape=(n_frames), optional

The simulation timestep corresponding to each frame, in steps. If not supplied, the numbers 0..n_frames will be written

box : np.ndarray, dtype=float32, shape=(n_frames, 3, 3), optional

The periodic box vectors of the simulation in each frame, in nanometers. If not supplied, the vectors (1,0,0), (0,1,0) and (0,0,1) will be written for each frame.

lambd : np.ndarray, dtype=np.float32, shape=(n_frames), optional

The alchemical lambda value at each frame. If not supplied, all zeros will be written.
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