openmmtools.multistate.ParallelTemperingAnalyzer

class openmmtools.multistate.ParallelTemperingAnalyzer(*args, unbias_restraint=True, restraint_energy_cutoff='auto', restraint_distance_cutoff='auto', n_equilibration_iterations=None, statistical_inefficiency=None, max_subset=100, **kwargs)

The ParallelTemperingAnalyzer is the analyzer for a simulation generated from a Parallel Tempering sampler simulation, implemented as an instance of the ReplicaExchangeAnalyzer as the sampler is a subclass of the yank.multistate.ReplicaExchangeSampler

Attributes:

effective_length

float: The length of the production data as a number of uncorrelated samples

has_log_weights

Return True if the storage has log weights, False otherwise

kT

Quantity of boltzmann constant times temperature of the phase in units of energy per mol

max_n_iterations

mbar

n_equilibration_iterations

int: The number of equilibration iterations.

n_iterations

int: The total number of iterations of the phase.

n_replicas

int: Number of replicas.

n_states

int: Number of sampled thermodynamic states.

name

User-readable string name of the phase

observables

List of observables that the instanced analyzer can compute/fetch.

reference_states

Tuple of reference states i and j for MultiPhaseAnalyzer instances

reporter

Sampler Reporter tied to this object.

restraint_distance_cutoff

restraint_energy_cutoff

statistical_inefficiency

float: The statistical inefficiency of the sampler.

unbias_restraint

use_full_trajectory

use_online_data

Get the online data flag

Methods

clear()	Reset all cached objects.
generate_mixing_statistics([number_equilibrated])	Compute and return replica mixing statistics.
get_effective_energy_timeseries([energies, ...])	Generate the effective energy (negative log deviance) timeseries that is generated for this phase.
get_enthalpy()	Compute the difference in enthalpy and error in that estimate from the MBAR object
get_entropy()	Compute the difference in entropy and error in that estimate from the MBAR object
get_free_energy()	Compute the free energy and error in free energy from the MBAR object
read_energies()	Extract energies from the ncfile and order them by replica, state, iteration.
read_logZ([iteration])	Extract logZ estimates from the ncfile, if present.
read_log_weights()	Extract log weights from the ncfile, if present.
reformat_energies_for_mbar(u_kln[, n_k])	Convert [replica, state, iteration] data into [state, total_iteration] data
show_mixing_statistics([cutoff, ...])	Print summary of mixing statistics.

See also

PhaseAnalyzer

ReplicaExchangeAnalyzer

__init__(*args, unbias_restraint=True, restraint_energy_cutoff='auto', restraint_distance_cutoff='auto', n_equilibration_iterations=None, statistical_inefficiency=None, max_subset=100, **kwargs)

The reporter provides the hook into how to read the data, all other options control where differences are measured from and how each phase interfaces with other phases.

Methods

__init__(*args[, unbias_restraint, ...])	The reporter provides the hook into how to read the data, all other options control where differences are measured from and how each phase interfaces with other phases.
clear()	Reset all cached objects.
generate_mixing_statistics([number_equilibrated])	Compute and return replica mixing statistics.
get_effective_energy_timeseries([energies, ...])	Generate the effective energy (negative log deviance) timeseries that is generated for this phase.
get_enthalpy()	Compute the difference in enthalpy and error in that estimate from the MBAR object
get_entropy()	Compute the difference in entropy and error in that estimate from the MBAR object
get_free_energy()	Compute the free energy and error in free energy from the MBAR object
read_energies()	Extract energies from the ncfile and order them by replica, state, iteration.
read_logZ([iteration])	Extract logZ estimates from the ncfile, if present.
read_log_weights()	Extract log weights from the ncfile, if present.
reformat_energies_for_mbar(u_kln[, n_k])	Convert [replica, state, iteration] data into [state, total_iteration] data
show_mixing_statistics([cutoff, ...])	Print summary of mixing statistics.

Attributes

effective_length	float: The length of the production data as a number of uncorrelated samples
has_log_weights	Return True if the storage has log weights, False otherwise
kT	Quantity of boltzmann constant times temperature of the phase in units of energy per mol
max_n_iterations	Analyzer helper descriptor of a cached value with a dependency graph.
mbar	Analyzer helper descriptor of a cached value with a dependency graph.
n_equilibration_iterations	int: The number of equilibration iterations.
n_iterations	int: The total number of iterations of the phase.
n_replicas	int: Number of replicas.
n_states	int: Number of sampled thermodynamic states.
name	User-readable string name of the phase
observables	List of observables that the instanced analyzer can compute/fetch.
reference_states	Tuple of reference states i and j for MultiPhaseAnalyzer instances
reporter	Sampler Reporter tied to this object.
restraint_distance_cutoff	Analyzer helper descriptor of a cached value with a dependency graph.
restraint_energy_cutoff	Analyzer helper descriptor of a cached value with a dependency graph.
statistical_inefficiency	float: The statistical inefficiency of the sampler.
unbias_restraint	Analyzer helper descriptor of a cached value with a dependency graph.
use_full_trajectory	Analyzer helper descriptor of a cached value with a dependency graph.
use_online_data	Get the online data flag