PostProcessing

This module collects some useful postprocessing functions that can be used in the Dataset class.

mppi.Datasets.PostProcessing.QE_get_energy(dataset)

Extract the total energy from the results dictionary of the dataset.

Parameters

dataset (Dataset) – the instance of Dataset

Returns

dictionary with the energy (in Hartree) for all the (computed) runs

of the dataset

Return type

dict

mppi.Datasets.PostProcessing.QE_get_gap(dataset)

Extract the value of the gap from the results dictionary of the dataset.

Parameters

dataset (Dataset) – the instance of Dataset

Returns

dictionary with the gap (in eV) for all the (computed) runs

of the dataset. Information on the nature of the gap (direct or indirect) are written on the screen.

Return type

dict

mppi.Datasets.PostProcessing.QE_parse_data(dataset)

Apply the PwParser to the elements of the results dictionary of the dataset.

Parameters

dataset (Dataset) – the instance of Dataset

Returns

dictionary with the parsed data for all the (computed) runs

of the dataset

Return type

dict

mppi.Datasets.PostProcessing.Yambo_parse_data(dataset)

Apply the YamboParser to the elements of the results dictionary of the dataset.

Parameters

dataset (Dataset) – the instance of Dataset

Returns

dictionary with the parsed data for all the (computed) runs

of the dataset

Return type

dict