NOE
This is part of the isdb module

Calculates NOE intensities as sums of 1/r^6, also averaging over multiple equivalent atoms or ambiguous NOE.

Each NOE is defined by two groups containing the same number of atoms, distances are calculated in pairs, transformed in 1/r^6, summed and saved as components.

\[ NOE() = (\frac{1}{N_{eq}}\sum_j^{N_{eq}} (\frac{1}{r_j^6})) \]

NOE can be used to calculate a Metainference score over one or more replicas using the intrinsic implementation of METAINFERENCE that is activated by DOSCORE.

Examples
In the following examples three noes are defined, the first is calculated based on the distances of atom 1-2 and 3-2; the second is defined by the distance 5-7 and the third by the distances 4-15,4-16,8-15,8-16. METAINFERENCE is activated using DOSCORE.
Click on the labels of the actions for more information on what each action computes
tested on master
noes: NOE ...
   
GROUPA1
the atoms involved in each of the contacts you wish to calculate.
=1,3
GROUPB1
the atoms involved in each of the contacts you wish to calculate.
=2,2
NOEDIST1
Add an experimental value for each NOE..
=0.6
GROUPA2
the atoms involved in each of the contacts you wish to calculate.
=5
GROUPB2
the atoms involved in each of the contacts you wish to calculate.
=7
NOEDIST2
Add an experimental value for each NOE..
=0.6
GROUPA3
the atoms involved in each of the contacts you wish to calculate.
=4,4,8,8
GROUPB3
the atoms involved in each of the contacts you wish to calculate.
=15,16,15,16
NOEDIST3
Add an experimental value for each NOE..
=0.6
DOSCORE
( default=off ) activate metainference
SIGMA_MEAN0
could not find this keyword
=1 ...
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
score the Metainference score
sigma uncertainty parameter
sigmaMean uncertainty in the mean estimate
neff effective number of replicas
acceptSigma MC acceptance for sigma values
noe the # NOE

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

Quantity Keyword Description
acceptScale SCALEDATA MC acceptance for scale value
acceptFT GENERIC MC acceptance for general metainference f tilde value
weight REWEIGHT weights of the weighted average
biasDer REWEIGHT derivatives with respect to the bias
scale SCALEDATA scale parameter
offset ADDOFFSET offset parameter
ftilde GENERIC ensemble average estimator
exp NOEDIST the # NOE experimental distance
The atoms involved can be specified using
GROUPA the atoms involved in each of the contacts you wish to calculate. Keywords like GROUPA1, GROUPA2, GROUPA3,... should be listed and one contact will be calculated for each ATOM keyword you specify.. You can use multiple instances of this keyword i.e. GROUPA1, GROUPA2, GROUPA3...
GROUPB the atoms involved in each of the contacts you wish to calculate. Keywords like GROUPB1, GROUPB2, GROUPB3,... should be listed and one contact will be calculated for each ATOM keyword you specify.. You can use multiple instances of this keyword i.e. GROUPB1, GROUPB2, GROUPB3...
Compulsory keywords
NOISETYPE ( default=MGAUSS ) functional form of the noise (GAUSS,MGAUSS,OUTLIERS,MOUTLIERS,GENERIC)
LIKELIHOOD ( default=GAUSS ) the likelihood for the GENERIC metainference model, GAUSS or LOGN
DFTILDE ( default=0.1 ) fraction of sigma_mean used to evolve ftilde
SCALE0 ( default=1.0 ) initial value of the scaling factor
SCALE_PRIOR ( default=FLAT ) either FLAT or GAUSSIAN
OFFSET0 ( default=0.0 ) initial value of the offset
OFFSET_PRIOR ( default=FLAT ) either FLAT or GAUSSIAN
SIGMA0 ( default=1.0 ) initial value of the uncertainty parameter
SIGMA_MIN ( default=0.0 ) minimum value of the uncertainty parameter
SIGMA_MAX ( default=10. ) maximum value of the uncertainty parameter
OPTSIGMAMEAN ( default=NONE ) Set to NONE/SEM to manually set sigma mean, or to estimate it on the fly
WRITE_STRIDE ( default=10000 ) write the status to a file every N steps, this can be used for restart/continuation
Options
NUMERICAL_DERIVATIVES ( default=off ) calculate the derivatives for these quantities numerically
DOSCORE ( default=off ) activate metainference
NOENSEMBLE ( default=off ) don't perform any replica-averaging
REWEIGHT ( default=off ) simple REWEIGHT using the ARG as energy
SCALEDATA ( default=off ) Set to TRUE if you want to sample a scaling factor common to all values and replicas
ADDOFFSET ( default=off ) Set to TRUE if you want to sample an offset common to all values and replicas
NOPBC

( default=off ) ignore the periodic boundary conditions when calculating distances

ARG the input for this action is the scalar output from one or more other actions. The particular scalars that you will use are referenced using the label of the action. If the label appears on its own then it is assumed that the Action calculates a single scalar value. The value of this scalar is thus used as the input to this new action. If * or *.* appears the scalars calculated by all the proceeding actions in the input file are taken. Some actions have multi-component outputs and each component of the output has a specific label. For example a DISTANCE action labelled dist may have three components x, y and z. To take just the x component you should use dist.x, if you wish to take all three components then use dist.*.More information on the referencing of Actions can be found in the section of the manual on the PLUMED Getting Started. Scalar values can also be referenced using POSIX regular expressions as detailed in the section on Regular Expressions. To use this feature you you must compile PLUMED with the appropriate flag.. You can use multiple instances of this keyword i.e. ARG1, ARG2, ARG3...
AVERAGING Stride for calculation of averaged weights and sigma_mean
SCALE_MIN minimum value of the scaling factor
SCALE_MAX maximum value of the scaling factor
DSCALE maximum MC move of the scaling factor
OFFSET_MIN minimum value of the offset
OFFSET_MAX maximum value of the offset
DOFFSET maximum MC move of the offset
REGRES_ZERO stride for regression with zero offset
DSIGMA maximum MC move of the uncertainty parameter
SIGMA_MEAN0 starting value for the uncertainty in the mean estimate
SIGMA_MAX_STEPS Number of steps used to optimise SIGMA_MAX, before that the SIGMA_MAX value is used
TEMP the system temperature - this is only needed if code doesn't pass the temperature to plumed
MC_STEPS number of MC steps
MC_CHUNKSIZE MC chunksize
STATUS_FILE write a file with all the data useful for restart/continuation of Metainference
SELECTOR name of selector
NSELECT range of values for selector [0, N-1]
RESTART allows per-action setting of restart (YES/NO/AUTO)
NOEDIST Add an experimental value for each NOE.. You can use multiple instances of this keyword i.e. NOEDIST1, NOEDIST2, NOEDIST3...