sarkas.tools.observables.RadialDistributionFunction#

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

Radial Distribution Function.

Variables

  • no_bins (int) – Number of bins.

  • dr_rdf (float) – Size of each bin.

Methods

RadialDistributionFunction.__init__()

RadialDistributionFunction.average_slices_data()

Calculate the average and standard deviation of the observable from the slices dataframe.

RadialDistributionFunction.calc_k_data()

Calculate and save Fourier space data.

RadialDistributionFunction.calc_nkt_slices_data()

Calculate n(k,t) for each slice.

RadialDistributionFunction.calc_slices_data()

RadialDistributionFunction.calc_vkt_slices_data()

Calculate v(k,t) for each slice.

RadialDistributionFunction.calculate_corr_times([...])

RadialDistributionFunction.compute()

Routine for computing the observable.

RadialDistributionFunction.compute_kt_data([...])

Calculate Time dependent Fourier space quantities.

RadialDistributionFunction.compute_sum_rule_integrals(...)

Compute integrals of the RDF used in sum rules.

RadialDistributionFunction.copy_params(params)

RadialDistributionFunction.create_dirs_filenames()

Create the directories and filenames where to save dataframes.

RadialDistributionFunction.from_dict(input_dict)

Update attributes from input dictionary.

RadialDistributionFunction.from_pickle()

Read the observable's info from the pickle file.

RadialDistributionFunction.grab_sim_data([pva])

Read in particles data into one large array.

RadialDistributionFunction.initialize_hdf()

RadialDistributionFunction.integrate_normalized_acf_squared(...)

Calculate the normalized correlation time as given by

RadialDistributionFunction.parse([acf_data])

Grab the pandas dataframe from the saved csv file.

RadialDistributionFunction.parse_acf()

RadialDistributionFunction.parse_k_data()

Read in the precomputed Fourier space data.

RadialDistributionFunction.parse_kt_data([...])

Read in the precomputed time dependent Fourier space data.

RadialDistributionFunction.plot([scaling, ...])

Plot the observable by calling the pandas.DataFrame.plot() function and save the figure.

RadialDistributionFunction.pretty_print_msg()

Create the message with the basic information of every observable

RadialDistributionFunction.save_acf_hdf()

RadialDistributionFunction.save_hdf()

RadialDistributionFunction.save_kt_hdf([...])

Save the \(n(\mathbf{k},t)\) and/or \(\mathbf{v}(\mathbf{k},t)\) data of each slice to disk.

RadialDistributionFunction.save_pickle()

Save the observable's info into a pickle file.

RadialDistributionFunction.setup(params[, ...])

Assign attributes from simulation's parameters.

RadialDistributionFunction.setup_init(params)

Assign Observables attributes and copy the simulation's parameters.

RadialDistributionFunction.setup_multirun_dirs()

Set the attributes postprocessing_dir and dump_dirs_list.

RadialDistributionFunction.update_args(**kwargs)

Update observable specific attributes and call update_finish() to save info.

RadialDistributionFunction.update_finish()

Update the slice_steps, CCF's and DSF's attributes, and save pickle file with observable's info.