The base workflow¶

The alchemlyb.workflows.base.WorkflowBase provides a basic API template for the workflow development. The workflow should be able to run in an automatic fashion.

>>> from alchemlyb.workflows.base import WorkflowBase
>>> workflow = WorkflowBase(units='kT', software='Gromacs', T=298,
    out='./', *args, **kwargs)
>>> workflow.run(*args, **kwargs)

Three main functions are provided such that the workflow could be run in a step-by-step fashion.

>>> from alchemlyb.workflows.base import WorkflowBase
>>> workflow = WorkflowBase(units='kT', software='Gromacs', T=298,
    out='./', *args, **kwargs)
>>> workflow.read(*args, **kwargs)
>>> workflow.preprocess(*args, **kwargs)
>>> workflow.estimate(*args, **kwargs)
>>> workflow.check_convergence(*args, **kwargs)
>>> workflow.plot(*args, **kwargs)

API Reference¶

class alchemlyb.workflows.base.WorkflowBase(units='kT', software='Gromacs', T=298, out='./', *args, **kwargs)¶

The base class for the Workflow.

This is the base class for the creation of new Workflow. The initialisation method takes in the MD engine, unit, temperature and output directory. The goal of the initialisation is to check the input files and store them in file_list such that they can be read by the read() method.

Parameters

units (string, optional) – The unit used for printing and plotting results. {‘kcal/mol’, ‘kJ/mol’, ‘kT’}. Default: ‘kT’.
software (string, optional) – The software used for generating input. {‘Gromacs’, ‘Amber’}
T (float, optional,) – Temperature in K. Default: 298.
out (string, optional) – Directory in which the output files produced by this script will be stored. Default: ‘./’.

file_list¶

A list of files to be read by the parser.

Type: list

run(*args, **kwargs)¶

Run the workflow in an automatic fashion.

This method would execute the read(), preprocess(), estimate(), check_convergence(), plot() sequentially such that the whole analysis could be done automatically.

This method takes in an arbitrary number of arguments and pass all of them to the underlying methods. The methods will be selecting the keywords that they would like to use.

Running this method would generate the resulting attributes for the user to retrieve the results.

u_nk_list¶

A list of pandas.DataFrame of u_nk.

Type: list

dHdl_list¶

A list of pandas.DataFrame of dHdl.

Type: list

u_nk_sample_list¶

A list of pandas.DataFrame of the subsampled u_nk.

Type: list

dHdl_sample_list¶

A list of pandas.DataFrame of the subsampled dHdl.

Type: list

result¶

The main result of the workflow.

Type: pandas.Dataframe

convergence¶

The result of the convergence analysis.

Type: pandas.Dataframe

read(*args, **kwargs)¶

The function that reads the files in file_list and parse them into u_nk and dHdl files.

u_nk_list¶

A list of pandas.DataFrame of u_nk.

Type: list

dHdl_list¶

A list of pandas.DataFrame of dHdl.

Type: list

preprocess(*args, **kwargs)¶

The function that subsample the u_nk and dHdl in u_nk_list and dHdl_list.

u_nk_sample_list¶

A list of pandas.DataFrame of the subsampled u_nk.

Type: list

dHdl_sample_list¶

A list of pandas.DataFrame of the subsampled dHdl.

Type: list

estimate(*args, **kwargs)¶

The function that runs the estimator based on u_nk_sample_list and dHdl_sample_list.

result¶

The main result of the workflow.

Type: pandas.Dataframe

check_convergence(*args, **kwargs)¶

The function for doing convergence analysis.

convergence¶

The result of the convergence analysis.

Type: pandas.Dataframe

plot(*args, **kwargs)¶: The function for producing any plots.