RelativeHybridTopologyProtocolResult

class openfe.protocols.openmm_rfe.RelativeHybridTopologyProtocolResult(**data)

Bases: ProtocolResult

Dict-like container for the output of a RelativeHybridTopologyProtocol

Methods

equilibration_iterations	Returns the number of equilibration iterations for each repeat of the calculation.
get_estimate	Average free energy difference of this transformation
get_forward_and_reverse_energy_analysis	Get a list of forward and reverse analysis of the free energies for each repeat using uncorrelated production samples.
get_individual_estimates	Return a list of tuples containing the individual free energy estimates and associated MBAR errors for each repeat.
get_overlap_matrices	Return a list of dictionary containing the MBAR overlap estimates calculated for each repeat.
get_replica_states	Returns the timeseries of replica states for each repeat.
get_replica_transition_statistics	The replica lambda state transition statistics for each repeat.
get_uncertainty	The uncertainty/error in the dG value: The std of the estimates of each independent repeat
production_iterations	Returns the number of uncorrelated production samples for each repeat of the calculation.

property data: dict[str, Any]

Aggregated data contents from multiple ProtocolDAGResult instances.

The structure of this data is specific to the Protocol subclass each ProtocolResult subclass corresponds to.

equilibration_iterations() → list[float]

Returns the number of equilibration iterations for each repeat of the calculation.

Returns:

equilibration_lengths

Return type:

list[float]

get_estimate() → Quantity

Average free energy difference of this transformation

Returns:

dG – The free energy difference between the first and last states. This is a Quantity defined with units.

Return type:

unit.Quantity

get_forward_and_reverse_energy_analysis() → list[dict[str, typing.Union[numpy.ndarray[typing.Any, numpy.dtype[+_ScalarType_co]], pint.util.Quantity]]]

Get a list of forward and reverse analysis of the free energies for each repeat using uncorrelated production samples.

The returned dicts have keys: ‘fractions’ - the fraction of data used for this estimate ‘forward_DGs’, ‘reverse_DGs’ - for each fraction of data, the estimate ‘forward_dDGs’, ‘reverse_dDGs’ - for each estimate, the uncertainty

The ‘fractions’ values are a numpy array, while the other arrays are Quantity arrays, with units attached.

Returns:

forward_reverse

Return type:

dict[str, Union[npt.NDArray, unit.Quantity]]

get_individual_estimates() → list[tuple[pint.util.Quantity, pint.util.Quantity]]

Return a list of tuples containing the individual free energy estimates and associated MBAR errors for each repeat.

Returns:

dGs – n_replicate simulation list of tuples containing the free energy estimates (first entry) and associated MBAR estimate errors (second entry).

Return type:

list[tuple[unit.Quantity]]

get_overlap_matrices() → list[dict[str, numpy.ndarray[typing.Any, numpy.dtype[+_ScalarType_co]]]]

Return a list of dictionary containing the MBAR overlap estimates calculated for each repeat.

Returns:

overlap_stats –

A list of dictionaries containing the following keys:

• scalar: One minus the largest nontrivial eigenvalue

• eigenvalues: The sorted (descending) eigenvalues of the overlap matrix

• matrix: Estimated overlap matrix of observing a sample from state i in state j

Return type:

list[dict[str, npt.NDArray]]

get_replica_states() → list[numpy.ndarray[typing.Any, numpy.dtype[+_ScalarType_co]]]

Returns the timeseries of replica states for each repeat.

Returns:

replica_states – List of replica states for each repeat

Return type:

List[npt.NDArray]

get_replica_transition_statistics() → list[dict[str, numpy.ndarray[typing.Any, numpy.dtype[+_ScalarType_co]]]]

The replica lambda state transition statistics for each repeat.

Note

This is currently only available in cases where a replica exchange simulation was run.

Returns:

repex_stats –

A list of dictionaries containing the following:

• eigenvalues: The sorted (descending) eigenvalues of the lambda state transition matrix

• matrix: The transition matrix estimate of a replica switching from state i to state j.

Return type:

list[dict[str, npt.NDArray]]

get_uncertainty() → Quantity

The uncertainty/error in the dG value: The std of the estimates of each independent repeat

production_iterations() → list[float]

Returns the number of uncorrelated production samples for each repeat of the calculation.

Returns:

production_lengths

Return type:

list[float]