electronic_minimization

py4vasp.calculation.electronic_minimization

(*args, **kwargs)

Access the convergence data for each electronic step.

The OSZICAR file written out by VASP stores information related to convergence. Please check the vasp-wiki for more details about the exact outputs generated for each combination of INCAR tags.

path

Returns the path from which the output is obtained.

plot

(*args, **kwargs)

Almost same as the to_graph() function.

All arguments will be passed to to_graph. If the to_graph() would produce multiple graphs this method will merge them into a single one.

print

()
Print a string representation of this instance.

read

(*args, **kwargs)
Convenient wrapper around to_dict. Check that function for examples and optional arguments.

selections

() → dict

Returns possible alternatives for this particular quantity VASP can produce.

The returned dictionary contains a single item with the name of the quantity mapping to all possible selections. Each of these selection may be passed to other functions of this quantity to select which output of VASP is used. Some quantities provide additional elements which can be passed as selection for other routines.

Returns

dict
The key indicates this quantity and the values possible choices for arguments to other functions of this quantity.

to_csv

(

  • *args,
  • filename: str | Path = None,
  • **kwargs

)

Writes the data to a csv file.

Writes out a csv file for data stored in a dataframe generated with the to_frame() method. Useful for creating external plots for further analysis.

If no filename is provided a default filename is deduced from the name of the class.

Note that the filename must be a keyword argument, i.e., you explicitly need to write filename=”name_of_file” because the arguments are passed on to the to_graph() method. Please check the documentation of that method to learn which arguments are allowed.

Parameters

filename: str | Path = None
Name of the csv file which the data is exported to.

to_dict

(selection: str = None) → dict

Extract convergence data from the HDF5 file and make it available in a dict

Parameters

selection: str = None
Choose from either iteration_number, free_energy, free_energy_change, bandstructure_energy_change, number_hamiltonian_evaluations, norm_residual, difference_charge_density to get specific columns of the OSZICAR file. In case no selection is provided, supply all columns.

Returns

dict
Contains a dict from the HDF5 related to OSZICAR convergence data

to_frame

(*args, **kwargs) → Dataframe

Convert data to pandas dataframe.

This will first convert use the to_graph() method to convert to a Graph. All arguments are passed to that method. The resulting graph is then converted to a dataframe.

Returns

Dataframe
Pandas dataframe corresponding to data in the graph

to_graph

(selection: str = ‘E’) → Graph

Graph the change in parameter with iteration number.

Parameters

selection: str = ‘E’
Choose strings consistent with the OSZICAR format

Returns

Graph
The Graph with the quantity plotted on y-axis and the iteration number of the x-axis.

to_image

(

  • *args,
  • filename = None,
  • **kwargs

)

Read the data and generate an image writing to the given filename.

The filetype is automatically deduced from the filename; possible are common raster (png, jpg) and vector (svg, pdf) formats. If no filename is provided a default filename is deduced from the name of the class and the picture has png format.

Note that the filename must be a keyword argument, i.e., you explicitly need to write filename=”name_of_file” because the arguments are passed on to the to_graph() method. Please check the documentation of that method to learn which arguments are allowed.

to_plotly

(*args, **kwargs)

Produces a graph and convertes it to a plotly figure.

The arguments to this function are passed on to the to_graph() method. Takes the resulting graph and converts it to a plotly figure.