Shortcut: LANDMARK_SELECT_FPS
| Module |
landmarks |
| Description |
Usage |
| Select a of landmarks from a large set of configurations using farthest point sampling. |
  |
Output components
This action can calculate the values in the following table when the associated keyword is included in the input for the action. These values can be referenced elsewhere in the input by using this Action's label followed by a dot and the name of the value required from the list below.
| Name |
Type |
Keyword |
Description |
| data |
matrix |
ARG |
the data that is being collected by this action |
| logweights |
vector |
ARG |
the logarithms of the weights of the data points |
| rectdissims |
matrix |
DISSIMILARITIES |
a rectangular matrix containing the distances between the landmark points and the rest of the points |
| sqrdissims |
matrix |
DISSIMILARITIES |
a square matrix containing the distances between each pair of landmark points |
Further details and examples
Select a of landmarks from a large set of configurations using farthest point sampling.
If you have collected a set of trajectory frames using COLLECT_FRAMES you can use this action to
select a subset of the configurations you have collected. This shortcut does this using FARTHEST_POINT_SAMPLING
the first point is thus selected 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. The following input demonstrates how you can use this method:
Click on the labels of the actions for more information on what each action computes
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. 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=1000
# cc: COLLECT_FRAMES ATOMS=1,2,3,4,5,6,7,8,9,10 ALIGN=OPTIMAL STRIDE=1 CLEAR=1000
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 points |
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=1000 CLEAR the frequency with which to clear all the accumulated data=1000
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=1000
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=1000
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=1000
# --- End of included input ---
llThe LANDMARK_SELECT_FPS action with label ll calculates the following quantities:| Quantity | Type | Description |
| ll_data | matrix | the data that is being collected by this action |
| ll_rectdissims | matrix | a rectangular matrix containing the distances between the landmark points and the rest of the points |
| ll_sqrdissims | matrix | a square matrix containing the distances between each pair of landmark points |
| ll_logweights | vector | the logarithms of the weights of the data points |
: LANDMARK_SELECT_FPSSelect a of landmarks from a large set of configurations using farthest point sampling. This action is a shortcut. More details ARGthe COLLECT_FRAMES action that you used to get the data=cc NLANDMARKSthe numbe rof landmarks you would like to create=100
# ll: LANDMARK_SELECT_FPS ARG=cc NLANDMARKS=100
The LANDMARK_SELECT_FPS action with label ll calculates the following quantities:| Quantity | Description |
| ll.data | the data that is being collected by this action |
| ll.logweights | the logarithms of the weights of the data points |
ll_allweightsThe CUSTOM action with label ll_allweights calculates the following quantities:| Quantity | Type | Description |
| ll_allweights | vector | the vector obtained by doing an element-wise application of an arbitrary function to the input vectors |
: LOGSUMEXPThis action takes the exponential of a vector of logarithms and divides each element of the vector by the sum of the exponentials. More details ARGthe vector of logweights that you would like to normalise using the logsumexp trick=cc_logweights
ll_cc_dataTThe TRANSPOSE action with label ll_cc_dataT calculates the following quantities:| Quantity | Type | Description |
| ll_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
ll_dissimsThe DISSIMILARITIES action with label ll_dissims calculates the following quantities:| Quantity | Type | Description |
| ll_dissims | matrix | the product of the two input matrices |
: DISSIMILARITIESCalculate the matrix of dissimilarities between a trajectory of atomic configurations. More details SQUARED calculate the squares of the dissimilarities (this option cannot be used with MATRIX_PRODUCT) ARGthe label of the two matrices from which the product is calculated=cc_data,ll_cc_dataT
ll_maskThe FARTHEST_POINT_SAMPLING action with label ll_mask calculates the following quantities:| Quantity | Type | Description |
| ll_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. More details ARGthe input matrix=ll_dissims NZEROSthe number of landmark points that you want to select=100
ll_dataThe SELECT_WITH_MASK action with label ll_data calculates the following quantities:| Quantity | Type | Description |
| ll_data | 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=ll_mask
ll_rmaskThe CREATE_MASK action with label ll_rmask calculates the following quantities:| Quantity | Type | Description |
| ll_rmask | vector | a vector of zeros and ones that is used that can be used to mask some of the elements in a time series |
: CREATE_MASKCreate a mask vector to use for landmark selection More details ARGthe label of the vector that you would like to construct a mask for=ll_allweights TYPEthe way the zeros are supposed to be set=nomask
ll_rectdissimsThe SELECT_WITH_MASK action with label ll_rectdissims calculates the following quantities:| Quantity | Type | Description |
| ll_rectdissims | 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=ll_dissims COLUMN_MASKan array with ones in the columns of the matrix that you want to discard=ll_mask ROW_MASKan array with ones in the rows of the matrix that you want to discard=ll_rmask
ll_sqrdissimsThe SELECT_WITH_MASK action with label ll_sqrdissims calculates the following quantities:| Quantity | Type | Description |
| ll_sqrdissims | 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=ll_dissims ROW_MASKan array with ones in the rows of the matrix that you want to discard=ll_mask COLUMN_MASKan array with ones in the columns of the matrix that you want to discard=ll_mask
ll_voronoiThe VORONOI action with label ll_voronoi calculates the following quantities:| Quantity | Type | Description |
| ll_voronoi | matrix | a matrix in which element ij is equal to one if the ij component of the input matrix is lower than all the ik elements of the matrix where k is not j and zero otherwise |
: VORONOIDo a voronoi analysis More details ARGthe distance/adjacency matrix that should be used to perform the voronoi analysis=ll_rectdissims
ll_allweightsTThe TRANSPOSE action with label ll_allweightsT calculates the following quantities:| Quantity | Type | Description |
| ll_allweightsT | 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=ll_allweights
ll_weightsTThe MATRIX_PRODUCT action with label ll_weightsT calculates the following quantities:| Quantity | Type | Description |
| ll_weightsT | matrix | the product of the two input matrices |
: MATRIX_PRODUCTCalculate the product of two matrices More details ARGthe label of the two matrices from which the product is calculated=ll_allweightsT,ll_voronoi
ll_weightsThe TRANSPOSE action with label ll_weights calculates the following quantities:| Quantity | Type | Description |
| ll_weights | 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=ll_weightsT
ll_logweightsThe CUSTOM action with label ll_logweights calculates the following quantities:| Quantity | Type | Description |
| ll_logweights | 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=ll_weights FUNCthe function you wish to evaluate=log(x) PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
ll_onesThe SELECT_WITH_MASK action with label ll_ones calculates the following quantities:| Quantity | Type | Description |
| ll_ones | vector | 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_ones MASKan array with ones in the components that you want to discard=ll_mask
# --- End of included input ---
DUMPPDBOutput PDB file. More details ATOMSvalue containing positions of atoms that should be output=ll_data 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 STRIDE the frequency with which the atoms should be output=1000
If you expand the shortcuts in the input above you will notice that the LANDMARK_SELECT_RANDOM shortcut creates a DISSIMILARITIES action
that calculates the distances between the input frames. We have to compute these dissimilarities in order to perform the farthest point sampling here so you cannot use the
NODISSIMILARITIES flag with this action. However, we also need the dissimilarities to compute the weights of the landmarks as this is done by performing a VORONOI analysis.
If you would like to turn off the computation of the VORONOI weights you can use the NOVORONOI flag.
If you have already computed the dissimilarities between the collected frames you can pass them in input to the LANDMARK_SELECT_FPS funtion as shown below:
Click on the labels of the actions for more information on what each action computes
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. 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=1000
# cc: COLLECT_FRAMES ATOMS=1,2,3,4,5,6,7,8,9,10 ALIGN=OPTIMAL STRIDE=1 CLEAR=1000
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 points |
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=1000 CLEAR the frequency with which to clear all the accumulated data=1000
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=1000
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=1000
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=1000
# --- End of included input ---
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
llThe LANDMARK_SELECT_FPS action with label ll calculates the following quantities:| Quantity | Type | Description |
| ll_data | matrix | the data that is being collected by this action |
| ll_rectdissims | matrix | a rectangular matrix containing the distances between the landmark points and the rest of the points |
| ll_sqrdissims | matrix | a square matrix containing the distances between each pair of landmark points |
| ll_logweights | vector | the logarithms of the weights of the data points |
: LANDMARK_SELECT_FPSSelect a of landmarks from a large set of configurations using farthest point sampling. This action is a shortcut. More details ARGthe COLLECT_FRAMES action that you used to get the data=cc DISSIMILARITIESthe matrix of dissimilarities if this is not provided the squared dissimilarities are calculated=dd NLANDMARKSthe numbe rof landmarks you would like to create=100
# ll: LANDMARK_SELECT_FPS ARG=cc DISSIMILARITIES=dd NLANDMARKS=100
The LANDMARK_SELECT_FPS action with label ll calculates the following quantities:| Quantity | Description |
| ll.data | the data that is being collected by this action |
| ll.logweights | the logarithms of the weights of the data points |
| ll.rectdissims | a rectangular matrix containing the distances between the landmark points and the rest of the points |
| ll.sqrdissims | a square matrix containing the distances between each pair of landmark points |
ll_allweightsThe CUSTOM action with label ll_allweights calculates the following quantities:| Quantity | Type | Description |
| ll_allweights | vector | the vector obtained by doing an element-wise application of an arbitrary function to the input vectors |
: LOGSUMEXPThis action takes the exponential of a vector of logarithms and divides each element of the vector by the sum of the exponentials. More details ARGthe vector of logweights that you would like to normalise using the logsumexp trick=cc_logweights
ll_maskThe FARTHEST_POINT_SAMPLING action with label ll_mask calculates the following quantities:| Quantity | Type | Description |
| ll_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. More details ARGthe input matrix=dd NZEROSthe number of landmark points that you want to select=100
ll_dataThe SELECT_WITH_MASK action with label ll_data calculates the following quantities:| Quantity | Type | Description |
| ll_data | 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=ll_mask
ll_rmaskThe CREATE_MASK action with label ll_rmask calculates the following quantities:| Quantity | Type | Description |
| ll_rmask | vector | a vector of zeros and ones that is used that can be used to mask some of the elements in a time series |
: CREATE_MASKCreate a mask vector to use for landmark selection More details ARGthe label of the vector that you would like to construct a mask for=ll_allweights TYPEthe way the zeros are supposed to be set=nomask
ll_rectdissimsThe SELECT_WITH_MASK action with label ll_rectdissims calculates the following quantities:| Quantity | Type | Description |
| ll_rectdissims | 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=dd COLUMN_MASKan array with ones in the columns of the matrix that you want to discard=ll_mask ROW_MASKan array with ones in the rows of the matrix that you want to discard=ll_rmask
ll_sqrdissimsThe SELECT_WITH_MASK action with label ll_sqrdissims calculates the following quantities:| Quantity | Type | Description |
| ll_sqrdissims | 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=dd ROW_MASKan array with ones in the rows of the matrix that you want to discard=ll_mask COLUMN_MASKan array with ones in the columns of the matrix that you want to discard=ll_mask
ll_voronoiThe VORONOI action with label ll_voronoi calculates the following quantities:| Quantity | Type | Description |
| ll_voronoi | matrix | a matrix in which element ij is equal to one if the ij component of the input matrix is lower than all the ik elements of the matrix where k is not j and zero otherwise |
: VORONOIDo a voronoi analysis More details ARGthe distance/adjacency matrix that should be used to perform the voronoi analysis=ll_rectdissims
ll_allweightsTThe TRANSPOSE action with label ll_allweightsT calculates the following quantities:| Quantity | Type | Description |
| ll_allweightsT | 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=ll_allweights
ll_weightsTThe MATRIX_PRODUCT action with label ll_weightsT calculates the following quantities:| Quantity | Type | Description |
| ll_weightsT | matrix | the product of the two input matrices |
: MATRIX_PRODUCTCalculate the product of two matrices More details ARGthe label of the two matrices from which the product is calculated=ll_allweightsT,ll_voronoi
ll_weightsThe TRANSPOSE action with label ll_weights calculates the following quantities:| Quantity | Type | Description |
| ll_weights | 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=ll_weightsT
ll_logweightsThe CUSTOM action with label ll_logweights calculates the following quantities:| Quantity | Type | Description |
| ll_logweights | 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=ll_weights FUNCthe function you wish to evaluate=log(x) PERIODICif the output of your function is periodic then you should specify the periodicity of the function=NO
ll_onesThe SELECT_WITH_MASK action with label ll_ones calculates the following quantities:| Quantity | Type | Description |
| ll_ones | vector | 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_ones MASKan array with ones in the components that you want to discard=ll_mask
# --- End of included input ---
DUMPPDBOutput PDB file. More details ATOMSvalue containing positions of atoms that should be output=ll_data 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 STRIDE the frequency with which the atoms should be output=1000
Notice that you can also read in dissimilarities from a file using a CONSTANT action and pass these directly to the LANDMARK_SELECT_FPS shortcut and avoid using COLLECT_FRAMES.
You can learn how to use landmark selection for dimensionality reduction calculations by working through this tutorial
Syntax
The following table describes the keywords and options that can be used with this action
| Keyword |
Type |
Default |
Description |
| NLANDMARKS |
compulsory |
none |
the numbe rof landmarks you would like to create |
| ARG |
optional |
not used |
the COLLECT_FRAMES action that you used to get the data |
| DISSIMILARITIES |
optional |
not used |
the matrix of dissimilarities if this is not provided the squared dissimilarities are calculated |
| SEED |
optional |
not used |
a random number seed |
| NOVORONOI |
optional |
false |
do not do a Voronoi analysis of the data to determine weights of final points |
| NODISSIMILARITIES |
optional |
false |
do not calculate the dissimilarities |
