sarkas.tools.transport.TransportCoefficients.plot_tc#

TransportCoefficients.plot_tc(time, acf_data, tc_data, acf_name, tc_name, figname, show=False)[source]#

Make dual plots with ACF and transport coefficient.

Parameters

  • time (numpy.ndarray) – Time array.

  • acf_data (numpy.ndarray) – Mean and Std of the ACF.

    Shape = (sarkas.tools.observables.Observable.slice_steps, 2).

  • tc_data (numpy.ndarray) – Mean and Std of the transport coefficient.

    Shape = (sarkas.tools.observables.Observable.slice_steps, 2).

  • acf_name (str) – y-Label of the ACF plot.

  • tc_name (str) – y-label of the transport coefficient plot.

  • figname (str) – Name with which to save the plot.

  • show (bool) – Flag for displaying the plot if using IPython or terminal.

Returns

  • fig (matplotlib.figure.Figure) – Figure object.

  • (ax1, ax2, ax3, ax4) (tuple) – Tuple with the axes handles.

    ax1 = ACF axes, ax2 = transport coefficient axes, ax3 = ax1.twiny(), ax4 = ax2.twiny()