Biased Sampling Methods
MetaQCD.BiasModule.calc_weights — MethodWeighting schemes based on the ones compared in
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00867
MetaQCD.BiasModule.Bias — TypeBias{TopChargeType,Smearing,BiasType,Weights,FileType}Container for bias potential and metadata.
Bias(p::ParameterSet, U::Gaugefield; instance=0)Create a Bias that holds general parameters of bias enhanced sampling, like the kind of CV, its smearing and filenames relevant to the bias. Also holds the specific kind of bias (Metadynamics, OPES or Parametric for now).
The instance keyword is used in case of PT-MetaD and multiple walkers to assign the correct usebias to each stream.
MetaQCD.BiasModule.Metadynamics — TypeMetadynamics <: AbstractBiasMetadynamics bias-enhanced sampler from https://arxiv.org/abs/cond-mat/0208352 .
Metadynamics(; symmetric=true, stride=1, cvlims=(-6, 6), biasfactor=Inf,
+Biased Sampling Methods · MetaQCD.jl Biased Sampling Methods
MetaQCD.BiasModule.calc_weights — MethodWeighting schemes based on the ones compared in
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.9b00867
sourceMetaQCD.BiasModule.Bias — TypeBias{TopChargeType,Smearing,BiasType,Weights,FileType}
Container for bias potential and metadata.
Bias(p::ParameterSet, U::Gaugefield; instance=0)
Create a Bias that holds general parameters of bias enhanced sampling, like the kind of CV, its smearing and filenames relevant to the bias. Also holds the specific kind of bias (Metadynamics, OPES or Parametric for now).
The instance keyword is used in case of PT-MetaD and multiple walkers to assign the correct usebias to each stream.
sourceMetaQCD.BiasModule.Metadynamics — TypeMetadynamics <: AbstractBias
Metadynamics bias-enhanced sampler from https://arxiv.org/abs/cond-mat/0208352 .
Metadynamics(; symmetric=true, stride=1, cvlims=(-6, 6), biasfactor=Inf,
bin_width=0.1, weight=0.01, penalty_weight=1000)
-Metadynamics(p::ParameterSet; instance=1)
Create an instance of a Metadynamics bias using the inputs or the parameters given in p.
Specifiable parameters
symmetric::Bool = true - If true, the bias is built symmetrically by updating for both cv and -cv at every update-iteration
stride::Int64 = 1 - Number of iterations between updates; must be >0
cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered
biasfactor::Float64 = Inf - Biasfactor for well-tempered Metadynamics; must be >1
bin_width::Float64 = 0.1 - Width of bins in histogram; must be >0
weight::Float64 = 0.01 - (Starting) Height of added Gaussians; must be positive
penalty_weight::Float64 = 1000 - Penalty when cv is outside of cvlims; must be positive
sourceMetaQCD.BiasModule.OPES — TypeOPES <: AbstractBias
OPES bias-enhanced sampler from https://arxiv.org/abs/1909.07250 .
OPES(; symmetric=true, stride=1, cvlims=(-6, 6), barrier=30,
+Metadynamics(p::ParameterSet; instance=1)
Create an instance of a Metadynamics bias using the inputs or the parameters given in p.
Specifiable parameters
symmetric::Bool = true - If true, the bias is built symmetrically by updating for both cv and -cv at every update-iteration
stride::Int64 = 1 - Number of iterations between updates; must be >0
cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered
biasfactor::Float64 = Inf - Biasfactor for well-tempered Metadynamics; must be >1
bin_width::Float64 = 0.1 - Width of bins in histogram; must be >0
weight::Float64 = 0.01 - (Starting) Height of added Gaussians; must be positive
penalty_weight::Float64 = 1000 - Penalty when cv is outside of cvlims; must be positive
sourceMetaQCD.BiasModule.OPES — TypeOPES <: AbstractBias
OPES bias-enhanced sampler from https://arxiv.org/abs/1909.07250 .
OPES(; symmetric=true, stride=1, cvlims=(-6, 6), barrier=30,
biasfactor=Inf, σ₀=0.1, σ_min=1e-6, fixed_σ=true, opes_epsilon=0.0,
no_Z=false, threshold=1.0, cutoff=0.0)
-OPES(p::ParameterSet; instance=1)
Create an instance of a OPES bias using the parameters given in p.
Specifiable parameters
symmetric::Bool = true - If true, the bias is built symmetrically by updating for both cv and -cv at every update-iteration
stride::Int64 = 1 - Number of iterations between updates; must be >0
cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered
barrier::Float64 = 30 - Estimate of height of action barriers
biasfactor::Float64 = Inf - Biasfactor for well-tempered OPES; must be >1
σ₀::Float64 = 0.1 - (Starting) width of kernels; must be >0
σ_min::Float64 = 1e-6 - Minimum width of kernels; must be >0
fixed_σ::Bool = true - If true, width if kernels decreases iteratively
ϵ::Float64 = exp(-barrier/(1-1/biasfactor)) - Determines maximum height of bias; must be >0
no_Z::Bool = false - If false normalization factor Z is dynamically adjusted
threshold::Float64 = 1.0 - Threshold distance for kernel merging; must be >0
cutoff::Float64 = sqrt(2barrier/(1-1/biasfactor)) - Cutoff value for kernels; must be >0
penalty::Float64 = exp(-0.5cutoff²) - Penalty for being outside kernel cutoff; must be >0
sourceMetaQCD.BiasModule.Parametric — TypeParametric <: AbstractBias
Bias-enhanced sampler that uses the parametrization from https://arxiv.org/pdf/2212.11665 up to first order.
Parametric(cvlims, penalty_weight, Q, A, Z)
-Parametric(p::ParameterSet; instance=1)
Create an instance of a static Parametric bias using the inputs or the parameters given in p.
Specifiable parameters
cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered
penalty_weight::Float64 = 1000 - Penalty when cv is outside of cvlims; must be positive
Q::Float64 = 0 - Quadratic term in the bias
A::Float64 = 0 - Amplitude of the cosine term in the bias
Z::Float64 = 0 - Frequency of the cosine term in the bias
sourceSettings
This document was generated with Documenter.jl version 1.3.0 on Thursday 28 November 2024. Using Julia version 1.9.4.
Create an instance of a OPES bias using the parameters given in p.
Specifiable parameters
symmetric::Bool = true - If true, the bias is built symmetrically by updating for both cv and -cv at every update-iteration stride::Int64 = 1 - Number of iterations between updates; must be >0 cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered barrier::Float64 = 30 - Estimate of height of action barriers biasfactor::Float64 = Inf - Biasfactor for well-tempered OPES; must be >1 σ₀::Float64 = 0.1 - (Starting) width of kernels; must be >0 σ_min::Float64 = 1e-6 - Minimum width of kernels; must be >0 fixed_σ::Bool = true - If true, width if kernels decreases iteratively ϵ::Float64 = exp(-barrier/(1-1/biasfactor)) - Determines maximum height of bias; must be >0 no_Z::Bool = false - If false normalization factor Z is dynamically adjusted threshold::Float64 = 1.0 - Threshold distance for kernel merging; must be >0 cutoff::Float64 = sqrt(2barrier/(1-1/biasfactor)) - Cutoff value for kernels; must be >0 penalty::Float64 = exp(-0.5cutoff²) - Penalty for being outside kernel cutoff; must be >0
MetaQCD.BiasModule.Parametric — TypeParametric <: AbstractBiasBias-enhanced sampler that uses the parametrization from https://arxiv.org/pdf/2212.11665 up to first order.
Parametric(cvlims, penalty_weight, Q, A, Z)
+Parametric(p::ParameterSet; instance=1)Create an instance of a static Parametric bias using the inputs or the parameters given in p.
Specifiable parameters
cvlims::NTuple{2, Float64} = (-6, 6) - Minimum and maximum of the explorable cv-space; must be ordered penalty_weight::Float64 = 1000 - Penalty when cv is outside of cvlims; must be positive Q::Float64 = 0 - Quadratic term in the bias A::Float64 = 0 - Amplitude of the cosine term in the bias Z::Float64 = 0 - Frequency of the cosine term in the bias