TI

The TI estimator is a simple implementation of thermodynamic integration that uses the trapezoid rule for integrating the space between \(\left<\frac{dH}{d\lambda}\right>\) values for each \(\lambda\) sampled.

API Reference

class alchemlyb.estimators.TI(verbose=False)

Thermodynamic integration (TI).

Parameters:verbose (bool, optional) – Set to True if verbose debug output is desired.

delta_f_

DataFrame – The estimated dimensionless free energy difference between each state.

d_delta_f_

DataFrame – The estimated statistical uncertainty (one standard deviation) in dimensionless free energy differences.

states_

list – Lambda states for which free energy differences were obtained.

fit(dHdl)

Compute free energy differences between each state by integrating dHdl across lambda values.

Parameters:dHdl (DataFrame) – dHdl[n,k] is the potential energy gradient with respect to lambda for each configuration n and lambda k.

get_params(deep=True)

Get parameters for this estimator.

Parameters:deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns:params – Parameter names mapped to their values. Return type:mapping of string to any

set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Returns: Return type:self