GaPFlow.md.LennardJones#

class GaPFlow.md.LennardJones(params)#

Bases: MolecularDynamics

Run MD simulations with LAMMPS for a pure LJ system.

__init__(params)#

Constructor.

Parameters:

params (dict) – Parameters to control the setup of the MD simulations (read from YAML input).

Methods

__init__(params)

Constructor.

build_input_files(dataset, location, X)

Builds LAMMPS input files based on GP inputs

read_output()

Read simulation output and returns observations and their standard error.

run(X_target, tag)

Run an MD simulation and store its input, metadata, and output into a dtool dataset.

Attributes

dtool_basepath

File location, where dtool datasets are written into (default is '/tmp/').

name

params

main_file

num_worker

is_mock

build_input_files(dataset, location, X)#
Builds LAMMPS input files based on GP inputs

and writes them to a dtool dataset.

Parameters:
  • dataset (dtoolcore.proto_dataset) – A proto_dataset object.

  • location (str) – Absolute path of the proto dataset.

  • X (Array) – Input (i.e. density, gap height, …)

property dtool_basepath#

File location, where dtool datasets are written into (default is ‘/tmp/’).

is_mock: bool#
main_file: str#
name = 'lj'#
num_worker: int#
params: dict#
read_output()#

Read simulation output and returns observations and their standard error.

run(X_target, tag)#

Run an MD simulation and store its input, metadata, and output into a dtool dataset.

This method is called from a Database instance when new training data is added e.g. during initialization or in an active learning simulation.

Parameters:
  • X_target (Array) – The training input.

  • tag (str) – A tag to attach to the dataset name.

Returns:

  • Array – Training observations

  • Array – Standard error of training observations