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1 : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 2 : Copyright (c) 2015-2023 The plumed team 3 : (see the PEOPLE file at the root of the distribution for a list of names) 4 : 5 : See http://www.plumed.org for more information. 6 : 7 : This file is part of plumed, version 2. 8 : 9 : plumed is free software: you can redistribute it and/or modify 10 : it under the terms of the GNU Lesser General Public License as published by 11 : the Free Software Foundation, either version 3 of the License, or 12 : (at your option) any later version. 13 : 14 : plumed is distributed in the hope that it will be useful, 15 : but WITHOUT ANY WARRANTY; without even the implied warranty of 16 : MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 : GNU Lesser General Public License for more details. 18 : 19 : You should have received a copy of the GNU Lesser General Public License 20 : along with plumed. If not, see <http://www.gnu.org/licenses/>. 21 : +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */ 22 : #include "matrixtools/MatrixOperationBase.h" 23 : #include "core/ActionRegister.h" 24 : #include "tools/Random.h" 25 : 26 : //+PLUMEDOC LANDMARKS FARTHEST_POINT_SAMPLING 27 : /* 28 : Select a set of landmarks using farthest point sampling. 29 : 30 : \par Examples 31 : 32 : */ 33 : //+ENDPLUMEDOC 34 : 35 : namespace PLMD { 36 : namespace landmarks { 37 : 38 : class FarthestPointSampling : public matrixtools::MatrixOperationBase { 39 : private: 40 : unsigned seed; 41 : unsigned nlandmarks; 42 : public: 43 : static void registerKeywords( Keywords& keys ); 44 : explicit FarthestPointSampling( const ActionOptions& ao ); 45 0 : unsigned getNumberOfDerivatives() override { return 0; } 46 : void prepare() override ; 47 : void calculate() override ; 48 0 : void apply() override {} 49 0 : double getForceOnMatrixElement( const unsigned& jrow, const unsigned& krow ) const { plumed_merror("this should not be called"); } 50 : }; 51 : 52 : PLUMED_REGISTER_ACTION(FarthestPointSampling,"FARTHEST_POINT_SAMPLING") 53 : 54 4 : void FarthestPointSampling::registerKeywords( Keywords& keys ) { 55 4 : matrixtools::MatrixOperationBase::registerKeywords( keys ); 56 8 : keys.add("compulsory","NZEROS","the number of landmark points that you want to select"); 57 8 : keys.add("compulsory","SEED","1234","a random number seed"); 58 8 : keys.setValueDescription("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"); 59 4 : } 60 : 61 1 : FarthestPointSampling::FarthestPointSampling( const ActionOptions& ao ): 62 : Action(ao), 63 1 : MatrixOperationBase(ao) 64 : { 65 1 : if( getPntrToArgument(0)->getShape()[0]!=getPntrToArgument(0)->getShape()[1] ) error("input to this argument should be a square matrix of dissimilarities"); 66 2 : parse("NZEROS",nlandmarks); parse("SEED",seed); 67 1 : log.printf(" selecting %d landmark points \n", nlandmarks ); 68 : 69 1 : std::vector<unsigned> shape(1); shape[0] = getPntrToArgument(0)->getShape()[0]; 70 1 : addValue( shape ); setNotPeriodic(); getPntrToComponent(0)->buildDataStore(); 71 1 : } 72 : 73 1 : void FarthestPointSampling::prepare() { 74 1 : Value* myval = getPntrToComponent(0); 75 1 : if( myval->getShape()[0]!=getPntrToArgument(0)->getShape()[0] ) { 76 1 : std::vector<unsigned> shape(1); shape[0] = getPntrToArgument(0)->getShape()[0]; myval->setShape(shape); 77 : } 78 4 : for(unsigned i=0; i<nlandmarks; ++i) myval->set( i, 0.0 ); 79 11 : for(unsigned i=nlandmarks; i<myval->getShape()[0]; ++i) myval->set( i, 1.0 ); 80 1 : } 81 : 82 1 : void FarthestPointSampling::calculate() { 83 1 : Value* myval=getPntrToComponent(0); unsigned npoints = getPntrToArgument(0)->getShape()[0]; 84 14 : for(unsigned i=0; i<npoints; ++i) myval->set( i, 1.0 ); 85 1 : std::vector<unsigned> landmarks( nlandmarks ); 86 : 87 : // Select first point at random 88 1 : Random random; random.setSeed(-seed); double rand=random.RandU01(); 89 1 : landmarks[0] = std::floor( npoints*rand ); myval->set( landmarks[0], 0 ); 90 : 91 : // Now find distance to all other points (N.B. We can use squared distances here for speed) 92 1 : Matrix<double> distances( nlandmarks, npoints ); Value* myarg = getPntrToArgument(0); 93 14 : for(unsigned i=0; i<npoints; ++i) distances(0,i) = myarg->get( landmarks[0]*npoints + i ); 94 : 95 : // Now find all other landmarks 96 3 : for(unsigned i=1; i<nlandmarks; ++i) { 97 : // Find point that has the largest minimum distance from the landmarks selected thus far 98 : double maxd=0; 99 28 : for(unsigned j=0; j<npoints; ++j) { 100 26 : double mind=distances(0,j); 101 39 : for(unsigned k=1; k<i; ++k) { 102 13 : if( distances(k,j)<mind ) { mind=distances(k,j); } 103 : } 104 26 : if( mind>maxd ) { maxd=mind; landmarks[i]=j; } 105 : } 106 2 : myval->set( landmarks[i], 0 ); 107 28 : for(unsigned k=0; k<npoints; ++k) distances(i,k) = myarg->get( landmarks[i]*npoints + k ); 108 : } 109 1 : } 110 : 111 : } 112 : }