GaPFlow.md.GoldAlkane

class GaPFlow.md.GoldAlkane(params)

Bases: MolecularDynamics

Run MD simulations with LAMMPS for n-alkanes confined between gold surfaces.

Input files are build with the help of ASE and moltemplate.

__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 = 'mol'

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