alchemlyb.estimators.MBAR

class alchemlyb.estimators.MBAR(maximum_iterations=10000, relative_tolerance=1e-07, initial_f_k=None, method='hybr', verbose=False)

Multi-state Bennett acceptance ratio (MBAR).

Parameters

  • maximum_iterations (int, optional) – Set to limit the maximum number of iterations performed.

  • relative_tolerance (float, optional) – Set to determine the relative tolerance convergence criteria.

  • initial_f_k (np.ndarray, float, shape=(K), optional) – Set to the initial dimensionless free energies to use as a guess (default None, which sets all f_k = 0).

  • method (str, optional, default="hybr") – The optimization routine to use. This can be any of the methods available via scipy.optimize.minimize() or scipy.optimize.root().

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

delta_f_

The estimated dimensionless free energy difference between each state.

Type

DataFrame

d_delta_f_

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

Type

DataFrame

theta_

The theta matrix.

Type

DataFrame

states_

Lambda states for which free energy differences were obtained.

Type

list

__init__(maximum_iterations=10000, relative_tolerance=1e-07, initial_f_k=None, method='hybr', verbose=False)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([maximum_iterations, …])

Initialize self.

fit(u_nk)

Compute overlap matrix of reduced potentials using multi-state Bennett acceptance ratio.

get_params([deep])

Get parameters for this estimator.

predict(u_ln)

set_params(**params)

Set the parameters of this estimator.

Attributes

overlap_matrix

MBAR overlap matrix.