sarkas.tools.transport.Diffusion#

class sarkas.tools.transport.Diffusion[source]#

The diffusion coefficient is calculated from the Green-Kubo formula

\[D_{\alpha} = \frac{1}{3 N_{\alpha}} \sum_{i}^{N_{\alpha}} \int_0^{\tau} dt \, \langle \mathbf v^{(\alpha)}_{i}(t) \cdot \mathbf v^{(\alpha)}_{i}(0) \rangle.\]

where \(\mathbf v_{i}^{(\alpha)}(t)\) is the velocity of particle \(i\) of species \(\alpha\). Notice that the diffusion coefficient is averaged over all \(N_{\alpha}\) particles.

Data is retrievable at dataframe and dataframe_slices.

Methods

Diffusion.__init__()

Diffusion.calculate_average_temperature(params)

Calculate the average temperature from the sarkas.tools.observables.Thermodynamics data.

Diffusion.compute(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula.

Diffusion.copy_params(params)

Diffusion.create_df_filenames()

Create paths of the filenames of the dataframes.

Diffusion.diffusion(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula.

Diffusion.electrical_conductivity(observable)

Calculate the transport coefficient from the Green-Kubo formula.

Diffusion.get_observable_data(observable)

Grab the autocorrelation function datasets by calling the observable's parse() method.

Diffusion.initialize_dataframes(observable)

Grab observables autocorrelation data and initialize the dataframes where to store the data.

Diffusion.interdiffusion(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula

Diffusion.make_directories()

Create directories where to save the transport coefficients.

Diffusion.parse(observable)

Read the HDF files containing the transport coefficients.

Diffusion.plot(observable[, display_plot])

Make a dual plot comparing the ACF and the Transport Coefficient by using the plot_tc() method.

Diffusion.plot_tc(time, acf_data, tc_data, ...)

Make dual plots with ACF and transport coefficient.

Diffusion.pretty_print()

Diffusion.pretty_print_msg()

Print to screen the location where data is stored and other relevant information.

Diffusion.save_hdf()

Save the HDF dataframes to disk in the TransportCoefficient folder.

Diffusion.setup(params, observable)

Parameters

Diffusion.time_stamp(message, timing)

Print out to screen elapsed times.

Diffusion.viscosity(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula