Action: FARTHEST_POINT_SAMPLING

Module	landmarks
Description	Usage
Select a set of landmarks using farthest point sampling.
output value	type
a vector which has as many elements as there are rows in the input matrix of dissimilarities	vector

Input

The arguments that serve as the input for this action are specified using one or more of the keywords in the following table.

Further details and examples

Select a set of landmarks using farthest point sampling.

This action is used within the LANDMARK_SELECT_FPS shortcut, which performs farthest point sampling. Farthest point sampling is a method of selecting a subset of input coordinates that works by selecting a first point at random. The remaining points are then selected by taking the unselected point in the input data set that is the furthest from all the points that have been selected thus far.

This particular action is designed to be used in conjunction with SELECT_WITH_MASK in the same way that CREATE_MASK is designed to be be used with that action. This action takes an $N\times N$ matrix of dissimilarities in input and outputs and $N$ dimensional vector whose elements are ones and zeros. As shown in the example input below, this output vector is passed to a SELECT_WITH_MASK using the MASK keyword.

The example below thus shows how this action is used in the LANDMARK_SELECT_FPS shortcut to select 100 landmark frames from the trajectory using farthest point sampling.

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

# This stores the positions of all the first 10 atoms in the system for later analysis
ccThe COLLECT_FRAMES action with label cc calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_data
matrix
the data that is being collected by this action
cc_logweights
vector
the logarithms of the weights of the data points: COLLECT_FRAMESCollect atomic positions or argument values from the trajectory for later analysis This action is a shortcut and it has hidden defaults. More details ATOMSlist of atomic positions that you would like to collect and store for later analysis=1,2,3,4,5,6,7,8,9,10 ALIGN if storing atoms how would you like the alignment to be done can be SIMPLE/OPTIMAL=OPTIMAL
The COLLECT_FRAMES action with label cc calculates the following quantities:
 Quantity   
 Description  
cc.data
the data that is being collected by this action
cc.logweights
the logarithms of the weights of the data pointscc: COLLECT_FRAMESCollect atomic positions or argument values from the trajectory for later analysis This action is a shortcut and uses the defaults shown here. More details ATOMSlist of atomic positions that you would like to collect and store for later analysis=1,2,3,4,5,6,7,8,9,10 ALIGN if storing atoms how would you like the alignment to be done can be SIMPLE/OPTIMAL=OPTIMAL  STRIDE the frequency with which data should be stored for analysis=1 CLEAR the frequency with which data should all be deleted and restarted=0
# PLUMED interprets the command:
# cc: COLLECT_FRAMES ATOMS=1,2,3,4,5,6,7,8,9,10 ALIGN=OPTIMAL
# as follows (Click the red comment above to revert to the short version of the input):
cc_getposxThe POSITION action with label cc_getposx calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_getposx.x
vector
the x-component of the atom position
cc_getposx.y
vector
the y-component of the atom position
cc_getposx.z
vector
the z-component of the atom position: POSITIONCalculate the components of the position of an atom or atoms. More details ATOMSthe atom numbers that you would like to use the positions of=1,2,3,4,5,6,7,8,9,10
cc_getposThe CONCATENATE action with label cc_getpos calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_getpos
vector
the concatenated vector/matrix that was constructed from the input values: CONCATENATEJoin vectors or matrices together More details ARGthe values that should be concatenated together to form the output vector=cc_getposx.x,cc_getposx.y,cc_getposx.z
cc_cposxThe MEAN action with label cc_cposx calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_cposx
scalar
the mean of all the elements in the input vector: MEANCalculate the arithmetic mean of the elements in a vector More details ARGthe values input to this function=cc_getposx.x PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_cposyThe MEAN action with label cc_cposy calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_cposy
scalar
the mean of all the elements in the input vector: MEANCalculate the arithmetic mean of the elements in a vector More details ARGthe values input to this function=cc_getposx.y PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_cposzThe MEAN action with label cc_cposz calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_cposz
scalar
the mean of all the elements in the input vector: MEANCalculate the arithmetic mean of the elements in a vector More details ARGthe values input to this function=cc_getposx.z PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_refxThe CUSTOM action with label cc_refx calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_refx
vector
the vector obtained by doing an element-wise application of an arbitrary function to the input vectors: CUSTOMCalculate a combination of variables using a custom expression. More details ARGthe values input to this function=cc_getposx.x,cc_cposx FUNCthe function you wish to evaluate=x-y PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_refyThe CUSTOM action with label cc_refy calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_refy
vector
the vector obtained by doing an element-wise application of an arbitrary function to the input vectors: CUSTOMCalculate a combination of variables using a custom expression. More details ARGthe values input to this function=cc_getposx.y,cc_cposy FUNCthe function you wish to evaluate=x-y PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_refzThe CUSTOM action with label cc_refz calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_refz
vector
the vector obtained by doing an element-wise application of an arbitrary function to the input vectors: CUSTOMCalculate a combination of variables using a custom expression. More details ARGthe values input to this function=cc_getposx.z,cc_cposz FUNCthe function you wish to evaluate=x-y PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_refThe CONCATENATE action with label cc_ref calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_ref
vector
the concatenated vector/matrix that was constructed from the input values: CONCATENATEJoin vectors or matrices together More details ARGthe values that should be concatenated together to form the output vector=cc_refx,cc_refy,cc_refz
cc_refposThe COLLECT action with label cc_refpos calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_refpos
matrix
the time series for the input quantity: COLLECTCollect data from the trajectory for later analysis More details TYPE required if you are collecting an object with rank>0=matrix ARGthe label of the value whose time series is being stored for later analysis=cc_ref STRIDE the frequency with which the data should be collected and added to the quantity being averaged=0 CLEAR the frequency with which to clear all the accumulated data=0
cc_refposTThe TRANSPOSE action with label cc_refposT calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_refposT
vector
the transpose of the input matrix: TRANSPOSECalculate the transpose of a matrix More details ARGthe label of the vector or matrix that should be transposed=cc_refpos
cc_rmsdThe RMSD action with label cc_rmsd calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_rmsd.dist
scalar
the RMSD distance the atoms have moved
cc_rmsd.disp
vector
the vector of displacements for the atoms: RMSD_VECTORCalculate the RMSD distance between the instaneous configuration and multiple reference configurations More details ARGthe labels of two actions that you are calculating the RMSD between=cc_getpos,cc_refpos DISPLACEMENT Calculate the vector of displacements instead of the length of this vector SQUARED  This should be set if you want mean squared displacement instead of RMSD  TYPE the manner in which RMSD alignment is performed=OPTIMAL
cc_fposThe COMBINE action with label cc_fpos calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_fpos
vector
the vector obtained by doing an element-wise application of a linear compbination to the input vectors: COMBINECalculate a polynomial combination of a set of other variables. More details ARGthe values input to this function=cc_refposT,cc_rmsd.disp PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
cc_dataThe COLLECT action with label cc_data calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_data
matrix
the time series for the input quantity: COLLECTCollect data from the trajectory for later analysis More details TYPE required if you are collecting an object with rank>0=matrix ARGthe label of the value whose time series is being stored for later analysis=cc_fpos STRIDE the frequency with which the data should be collected and added to the quantity being averaged=1 CLEAR the frequency with which to clear all the accumulated data=0
cc_cweightThe CONSTANT action with label cc_cweight calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_cweight
scalar
the constant value that was read from the plumed input: CONSTANTCreate a constant value that can be passed to actions More details VALUEthe single number that you would like to store=0
cc_logweightsThe COLLECT action with label cc_logweights calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_logweights
vector
the time series for the input quantity: COLLECTCollect data from the trajectory for later analysis More details ARGthe label of the value whose time series is being stored for later analysis=cc_cweight STRIDE the frequency with which the data should be collected and added to the quantity being averaged=1 CLEAR the frequency with which to clear all the accumulated data=0
cc_oneThe CONSTANT action with label cc_one calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_one
scalar
the constant value that was read from the plumed input: CONSTANTCreate a constant value that can be passed to actions More details VALUEthe single number that you would like to store=1
cc_onesThe COLLECT action with label cc_ones calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_ones
vector
the time series for the input quantity: COLLECTCollect data from the trajectory for later analysis More details ARGthe label of the value whose time series is being stored for later analysis=cc_one STRIDE the frequency with which the data should be collected and added to the quantity being averaged=1 CLEAR the frequency with which to clear all the accumulated data=0
# --- End of included input --- 
# We now compute the dissimilarities between these frames
cc_dataTThe TRANSPOSE action with label cc_dataT calculates the following quantities:
 Quantity   
 Type   
 Description  
cc_dataT
matrix
the transpose of the input matrix: TRANSPOSECalculate the transpose of a matrix More details ARGthe label of the vector or matrix that should be transposed=cc_data
ddThe DISSIMILARITIES action with label dd calculates the following quantities:
 Quantity   
 Type   
 Description  
dd
matrix
the product of the two input matrices: DISSIMILARITIESCalculate the matrix of dissimilarities between a trajectory of atomic configurations. More details ARGthe label of the two matrices from which the product is calculated=cc_data,cc_dataT

# Create a mask that will be used to create our landmark data
maskThe FARTHEST_POINT_SAMPLING action with label mask calculates the following quantities:
 Quantity   
 Type   
 Description  
mask
vector
a vector which has as many elements as there are rows in the input matrix of dissimilarities. NZEROS of the elements in this vector are equal to one, the rest of the elements are equal to zero.  The nodes that have elements equal to one are the NZEROS points that are farthest appart according to the input dissimilarities: FARTHEST_POINT_SAMPLINGSelect a set of landmarks using farthest point sampling. This action has hidden defaults. More details ARGthe input matrix=dd NZEROSthe number of landmark points that you want to select=100
mask: FARTHEST_POINT_SAMPLINGSelect a set of landmarks using farthest point sampling. This action uses the defaults shown here. More details ARGthe input matrix=dd NZEROSthe number of landmark points that you want to select=100  SEED a random number seed=1234

# These are the landmark points
landmarksThe SELECT_WITH_MASK action with label landmarks calculates the following quantities:
 Quantity   
 Type   
 Description  
landmarks
matrix
a vector/matrix of values that is obtained using a mask to select elements of interest: SELECT_WITH_MASKUse a mask to select elements of an array More details ARGthe label for the value upon which you are going to apply the mask=cc_data ROW_MASKan array with ones in the rows of the matrix that you want to discard=mask

# Output the landmarks to a file
DUMPPDBOutput PDB file. More details ATOMSvalue containing positions of atoms that should be output=landmarks ATOM_INDICESthe indices of the atoms in your PDB output=1,2,3,4,5,6,7,8,9,10 FILEthe name of the file on which to output these quantities=traj.pdb

This only saves the coordinates of the landmark points. If you look at the shortcuts in the documentation for LANDMARK_SELECT_FPS you can see how the shortcut also saves information on the dissimilarities between the landmarks, the dissimilarities between the landmarks and all the other points and the weights of the landmarks, which are determined using a VORONOI analysis.

Syntax

The following table describes the keywords and options that can be used with this action