sarkas.tools.observables.ElectricCurrent#

class sarkas.tools.observables.ElectricCurrent[source]#

Electric Current Auto-correlation function.

Methods

`ElectricCurrent.__init__`()
`ElectricCurrent.average_slices_data`()	Average and std over the slices.
`ElectricCurrent.calc_k_data`()	Calculate and save Fourier space data.
`ElectricCurrent.calc_kt_data`([nkt_flag, ...])	Calculate Time dependent Fourier space quantities.
`ElectricCurrent.calculate_run_slices_data`()
`ElectricCurrent.compute`()	Calculate the observable (and its autocorrelation function).
`ElectricCurrent.create_dirs_filenames`()
`ElectricCurrent.from_dict`(input_dict)	Update attributes from input dictionary.
`ElectricCurrent.grab_sim_data`([pva])	Read in particles data
`ElectricCurrent.parse`()	Grab the pandas dataframe from the saved csv file.
`ElectricCurrent.parse_k_data`()	Read in the precomputed Fourier space data.
`ElectricCurrent.parse_kt_data`([nkt_flag, ...])	Read in the precomputed time dependent Fourier space data.
`ElectricCurrent.plot`([scaling, acf, ...])	Plot the observable by calling the pandas.DataFrame.plot() function and save the figure.
`ElectricCurrent.read_pickle`()	Read the observable's info from the pickle file.
`ElectricCurrent.save_hdf`()
`ElectricCurrent.save_pickle`()	Save the observable's info into a pickle file.
`ElectricCurrent.setup`(params[, phase, no_slices])	Assign attributes from simulation's parameters.
`ElectricCurrent.setup_init`(params[, phase, ...])	Assign Observables attributes and copy the simulation's parameters.
`ElectricCurrent.setup_multirun_dirs`()	Set the attributes postprocessing_dir and dump_dirs_list.
`ElectricCurrent.time_stamp`(message, timing)	Print to screen the elapsed time of the calculation.
`ElectricCurrent.update_args`(**kwargs)	Update observable specific attributes and call `update_finish()` to save info.
`ElectricCurrent.update_finish`()	Update the `slice_steps`, CCF's and DSF's attributes, and save pickle file with observable's info.