lammpsio

Tools for working with LAMMPS data and dump files.

lammpsio is a pure Python package that can be installed using pip:

pip install lammpsio

Snapshot

The particle configuration is stored in a Snapshot. A Snapshot holds the data for N particles, the simulation Box, and the timestep. The Box follows the LAMMPS conventions for its shape and bounds. Here is a 3-particle configuration in an orthorhombic box centered at the origin at step 100:

box = lammpsio.Box((-2,-3,-4), (2,3,4))
snapshot = lammpsio.Snapshot(3, box, step=100)

These constructor arguments are available as attributes:

• N: number of particles (int)
• box: bounding box (Box)
• step: timestep counter (int)

The data contained in a Snapshot per particle is:

• position: (N,3) array of coordinates (dtype: numpy.float64, default: (0,0,0))
• image: (N,3) array of periodic image indexes (dtype: numpy.int32, default: (0,0,0))
• velocity: (N,3) array of velocities (dtype: numpy.float64, default: (0,0,0))
• molecule: (N,) array of molecule indexes (dtype: numpy.int32, default: 0)
• typeid: (N,) array of type indexes (dtype: numpy.int32, default: 1)
• mass: (N,) array of masses (dtype: numpy.float64, default: 1)
• charge: (N,) array of charges (dtype: numpy.float64, default: 0)

All values of indexes will follow the LAMMPS 1-indexed convention, but the arrays themselves are 0-indexed.

The Snapshot will lazily initialize these per-particle arrays as they are accessed to save memory. Hence, accessing a per-particle property will allocate it to default values. If you want to check if an attribute has been set, use the corresponding has_ method instead (e.g., has_position()):

snapshot.position = [[0,0,0],[1,-1,1],[1.5,2.5,-3.5]]
snapshot.typeid[2] = 2
if not snapshot.has_mass():
    snapshot.mass = [2.,2.,10.]

Data files

A LAMMPS data file is represented by a DataFile. The file must be explicitly read() to get a Snapshot:

f = lammpsio.DataFile("config.data")
snapshot = f.read()

The atom_style will be read from the comment in the Atoms section of the file. If it is not present, it must be specified in the DataFile. If atom_style is specified and also present in the file, the two must match or an error will be raised.

There are many sections that can be stored in a data file, but lammpsio does not currently understand all of them. You can check DataFile.known_headers, DataFile.unknown_headers, DataFile.known_bodies and DataFile.unknown_bodies for lists of what is currently supported.

A Snapshot can be written using the create() method:

f = lammpsio.DataFile.create("config2.data", snapshot)

A DataFile corresponding to the new file is returned by create().

Dump files

A LAMMPS dump file is represented by a DumpFile. The actual file format is very flexible, so a schema needs to be specified to parse it.

traj = lammpsio.DumpFile(
        filename="atoms.lammpstrj",
        schema={"id": 0, "typeid": 1, "position": (2, 3, 4)}
        )

Valid keys for the schema match the names and shapes in the Snapshot. The keys requiring only 1 column index are: id, typeid, molecule, charge, and mass. The keys requiring 3 column indexes are position, velocity, and image.

A DumpFile is iterable, so you can use it to go through all the snapshots of a trajectory:

for snap in traj:
    print(snap.step)

You can also get the number of snapshots in the DumpFile, but this does require reading the entire file: so use with caution!

num_frames = len(traj)

Random access to snapshots is not currently implemented, but it may be added in future. If you want to randomly access snapshots, you should load the whole file into a list:

snaps = [snap for snap in traj]
print(snaps[3].step)

Keep in the mind that the memory requirements for this can be huge!

A DumpFile can be created from a list of snapshots:

t = lammpsio.DumpFile.create("atoms.lammpstrj", schema, snaps)

The object representing the new file is returned and can be used.