mdsuite.calculators.einstein_diffusion_coefficients module

MDSuite: A Zincwarecode package.

License

This program and the accompanying materials are made available under the terms of the Eclipse Public License v2.0 which accompanies this distribution, and is available at https://www.eclipse.org/legal/epl-v20.html

SPDX-License-Identifier: EPL-2.0

Copyright Contributors to the Zincwarecode Project.

Contact Information

email: zincwarecode@gmail.com github: https://github.com/zincware web: https://zincwarecode.com/

Citation

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Summary

Module for the computation of self-diffusion coefficients using the Einstein method.

class mdsuite.calculators.einstein_diffusion_coefficients.Args(data_range: int, correlation_time: int, atom_selection: np.s_, tau_values: np.s_, molecules: bool, species: list, fit_range: int)[source]

Bases: object

Data class for the saved properties.

atom_selection: np.s_
correlation_time: int
data_range: int
fit_range: int
molecules: bool
species: list
tau_values: np.s_
class mdsuite.calculators.einstein_diffusion_coefficients.EinsteinDiffusionCoefficients(**kwargs)[source]

Bases: TrajectoryCalculator, ABC

Class for the Einstein diffusion coefficient implementation.

msd_array

MSd data updated during each ensemble computation.

Type:

np.ndarray

Examples

project.experiment.run.EinsteinDiffusionCoefficients(data_range=500,

plot=True, correlation_time=10)

ensemble_operation(ensemble)[source]

Calculate and return the msd.

Parameters:

ensemble (tf.Tensor) – An ensemble of data to be operated on.

Return type:

MSD of the tensor_values.

fit_diff_coeff()[source]

Apply unit conversion, fit line to the data, prepare for database storage.

plot_data(data)[source]

Plot the Einstein fits.

Parameters:

data

run_calculator()[source]

Run analysis.