METAINFERENCE

This is part of the isdb module |

Calculates the Metainference energy for a set of experimental data.

Metainference [21] is a Bayesian framework to model heterogeneous systems by integrating prior information with noisy, ensemble-averaged data. Metainference models a system and quantifies the level of noise in the data by considering a set of replicas of the system.

Calculated experimental data are given in input as ARG while reference experimental values can be given either from fixed components of other actions using PARARG or as numbers using PARAMETERS. The default behavior is that of averaging the data over the available replicas, if this is not wanted the keyword NOENSEMBLE prevent this averaging.

Metadynamics Metainference [22] or more in general biased Metainference requires the knowledge of biasing potential in order to calculate the weighted average. In this case the value of the bias can be provided as the last argument in ARG and adding the keyword REWEIGHT. To avoid the noise resulting from the instantaneous value of the bias the weight of each replica can be averaged over a give time using the keyword AVERAGING.

The data can be averaged by using multiple replicas and weighted for a bias if present. The functional form of Metainference can be chosen among four variants selected with NOISE=GAUSS,MGAUSS,OUTLIERS,MOUTLIERS,GENERIC which correspond to modelling the noise for the arguments as a single gaussian common to all the data points, a gaussian per data point, a single long-tailed gaussian common to all the data points, a log-tailed gaussian per data point or using two distinct noises as for the most general formulation of Metainference. In this latter case the noise of the replica-averaging is gaussian (one per data point) and the noise for the comparison with the experimental data can chosen using the keyword LIKELIHOOD between gaussian or log-normal (one per data point), furthermore the evolution of the estimated average over an infinite number of replicas is driven by DFTILDE.

As for Metainference theory there are two sigma values: SIGMA_MEAN0 represent the error of calculating an average quantity using a finite set of replica and should be set as small as possible following the guidelines for replica-averaged simulations in the framework of the Maximum Entropy Principle. Alternatively, this can be obtained automatically using the internal sigma mean optimization as introduced in [84] (OPTSIGMAMEAN=SEM), in this second case sigma_mean is estimated from the maximum standard error of the mean either over the simulation or over a defined time using the keyword AVERAGING. SIGMA_BIAS is an uncertainty parameter, sampled by a MC algorithm in the bounded interval defined by SIGMA_MIN and SIGMA_MAX. The initial value is set at SIGMA0. The MC move is a random displacement of maximum value equal to DSIGMA. If the number of data point is too large and the acceptance rate drops it is possible to make the MC move over mutually exclusive, random subset of size MC_CHUNKSIZE and run more than one move setting MC_STEPS in such a way that MC_CHUNKSIZE*MC_STEPS will cover all the data points.

Calculated and experimental data can be compared modulo a scaling factor and/or an offset using SCALEDATA and/or ADDOFFSET, the sampling is obtained by a MC algorithm either using a flat or a gaussian prior setting it with SCALE_PRIOR or OFFSET_PRIOR.

- Examples

In the following example we calculate a set of RDC, take the replica-average of them and comparing them with a set of experimental values. RDCs are compared with the experimental data but for a multiplication factor SCALE that is also sampled by MC on-the-fly

Click on the labels of the actions for more information on what each action computes

rdc:RDC ...SCALE=0.0001compulsory keyword ( default=1. )Add the scaling factor to take into account concentration and other effects.GYROM=-72.5388compulsory keyword ( default=1. )Add the product of the gyromagnetic constants for the bond.ATOMS1=22,23the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS2=25,27the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS3=29,31the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS4=33,34 ...the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.spe:METAINFERENCE ...ARG=the input for this action is the scalar output from one or more other actions.rdc.*NOISETYPE=MGAUSScompulsory keyword ( default=MGAUSS )functional form of the noise (GAUSS,MGAUSS,OUTLIERS,MOUTLIERS,GENERIC)PARAMETERS=1.9190,2.9190,3.9190,4.9190reference values for the experimental dataSCALEDATA( default=off ) Set to TRUE if you want to sample a scaling factor common to all values and replicasSCALE0=1could not find this keywordSCALE_MIN=0.1minimum value of the scaling factorSCALE_MAX=3maximum value of the scaling factorDSCALE=0.01maximum MC move of the scaling factorSIGMA0=0.01could not find this keywordSIGMA_MIN=0.00001compulsory keyword ( default=0.0 )minimum value of the uncertainty parameterSIGMA_MAX=3compulsory keyword ( default=10. )maximum value of the uncertainty parameterDSIGMA=0.01maximum MC move of the uncertainty parameterSIGMA_MEAN0=0.001 ... PRINTcould not find this keywordARG=the input for this action is the scalar output from one or more other actions.spe.biasFILE=BIASthe name of the file on which to output these quantitiesSTRIDE=1compulsory keyword ( default=1 )the frequency with which the quantities of interest should be output

in the following example instead of using one uncertainty parameter per data point we use a single uncertainty value in a long-tailed gaussian to take into account for outliers, furthermore the data are weighted for the bias applied to other variables of the system.

Click on the labels of the actions for more information on what each action computes

rdc:RDC ...SCALE=0.0001compulsory keyword ( default=1. )Add the scaling factor to take into account concentration and other effects.GYROM=-72.5388compulsory keyword ( default=1. )Add the product of the gyromagnetic constants for the bond.ATOMS1=22,23the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS2=25,27the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS3=29,31the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.ATOMS4=33,34 ...the couple of atoms involved in each of the bonds for which you wish to calculate the RDC.cv1:TORSIONATOMS=1,2,3,4the four atoms involved in the torsional anglecv2:TORSIONATOMS=2,3,4,5the four atoms involved in the torsional anglemm:METADARG=the input for this action is the scalar output from one or more other actions.cv1,cv2HEIGHT=0.5the heights of the Gaussian hills.SIGMA=0.3,0.3compulsory keywordthe widths of the Gaussian hillsPACE=200compulsory keywordthe frequency for hill additionBIASFACTOR=8use well tempered metadynamics and use this bias factor.WALKERS_MPI( default=off ) Switch on MPI version of multiple walkers - not compatible with WALKERS_* options other than WALKERS_DIRspe:METAINFERENCE ... #SETTINGS NREPLICAS=2ARG=the input for this action is the scalar output from one or more other actions.rdc.*,mm.biasREWEIGHT( default=off ) simple REWEIGHT using the latest ARG as energyNOISETYPE=OUTLIERScompulsory keyword ( default=MGAUSS )functional form of the noise (GAUSS,MGAUSS,OUTLIERS,MOUTLIERS,GENERIC)PARAMETERS=1.9190,2.9190,3.9190,4.9190reference values for the experimental dataSCALEDATA( default=off ) Set to TRUE if you want to sample a scaling factor common to all values and replicasSCALE0=1could not find this keywordSCALE_MIN=0.1minimum value of the scaling factorSCALE_MAX=3maximum value of the scaling factorDSCALE=0.01maximum MC move of the scaling factorSIGMA0=0.01could not find this keywordSIGMA_MIN=0.00001compulsory keyword ( default=0.0 )minimum value of the uncertainty parameterSIGMA_MAX=3compulsory keyword ( default=10. )maximum value of the uncertainty parameterDSIGMA=0.01maximum MC move of the uncertainty parameterSIGMA_MEAN0=0.001 ...could not find this keyword

- Glossary of keywords and components

- Description of components

By default this Action calculates the following quantities. These quantities can be referenced elsewhere in the input by using this Action's label followed by a dot and the name of the quantity required from the list below.

Quantity | Description |

bias | the instantaneous value of the bias potential |

sigma | uncertainty parameter |

sigmaMean | uncertainty in the mean estimate |

neff | effective number of replicas |

acceptSigma | MC acceptance for sigma values |

In addition the following quantities can be calculated by employing the keywords listed below

Quantity | Keyword | Description |

acceptScale | SCALEDATA | MC acceptance fo |